STUDY OF THIN-WALL INJECTION MOLDING

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the Graduate School of

The Ohio State University

By

Guojun Xu, M.E.

*****

The Ohio State University

2004

Dissertation Committee:

Professor Kurt W. Koelling, Adviser

Professor L. James Lee

Professor Jose M. Castro

Approved by

Adviser Department of Chemical Engineering

ii

ABSTRACT

Thin-wall injection molding has received increasing attention over the past few

years due to economic and environmental concerns. However, due to the difficulties

encountered in the thin-wall molding process, systematic investigation is lacking in

machine performance, mold design/manufacture requirement, molding characteristics,

computer aided engineering (CAE) simulation, part quality and part design criteria.

Furthermore, the combination of viscoelastic materials, complex molding geometry and

cyclic processing conditions has generated some problems, such as flow marks, polymer

degradation, sink marks and warpage, under high-speed and high-pressure injection

molding. So it is very important to design, operate, and control thin-wall molding

optimally to guarantee part quality as well as reduce cost.

In this study, alternate and synchronous dull and glossy flow marks, two surface

quality problems, were studied. For the alternate flow marks, the effect of polymer

rheology, mold geometry, operating variables, and mold surface coatings on the

appearance of the flow marks was studied. The flow marks occurred above a critical

wall shear stress, but disappeared at high injection speeds. Mold geometry and mold

temperature were found to affect the wavelength and the width of the flow marks, while

melt temperature did not have much effect. Slip was not the cause of the generation of

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the alternate flow marks. For synchronous dull and glossy flow marks, the effect of

operating parameters, mold geometry, and mold surface coatings on the flow marks was

studied. The flow marks occurred above a certain flow front velocity, but were less

visible as the mold temperature was increased. It was also found that mold surface

coatings did not eliminate the flow marks. The generation of these flow marks was

explained by an entry viscoelastic flow instability.

Furthermore, thin-wall injection molding with micro-features was investigated.

The filling length in microchannels was measured and compared with simulation. The

heat transfer coefficient was found to be very sensitive to the filling length prediction. In

order to investigate the effect of input properties on the simulation output, mold cavity

pressure was studied. The goal was to understand the effect of pressure-dependent

viscosity, heat capacity, heat transfer coefficient, juncture pressure loss and pvT-data on

cavity pressure and pressure drop prediction, and evaluate the importance of each

parameter. The cavity pressure and pressure drop were measured experimentally and

compared. Furthermore, the method to improve the prediction accuracy was discussed

to help design and predict.

As the increasing use of plastics, the plastics waste has become a main concern.

The final part of the research focuses on the mechanical and rheological properties of

virgin and recycled high impact polystyrene materials. In this study, we describe our

progress in evaluating the viability of reusing post-consumer and virgin polymer blends

of HIPS from electronics equipment housings. Plastics reuse challenges are briefly

reviewed, and experimental results, such as rheological properties, mechanical

iv

properties, molecular weight and morphology of different blends, are summarized and

discussed for reuse of HIPS. Finally, the study introduces a new approach to determine

initial processing parameters for thin-wall injection molding of post-consumer resin.

v

This dissertation is dedicated to my family.

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ACKNOWLEDGMENTS

I would like to express sincere gratitude to my adviser, Dr. Kurt W. Koelling, for

his priceless guidance, encouragement, and support throughout this work. I also would

like to thank Dr. Julie Ann Stuart and Dr. Blaine Lilly for their instruction,

encouragement and support. Special thanks go to Dr. L. James Lee for his considerable

advice and help. I wish to thank Dr. David Tomasko, Dr. Jose Castro, and Dr. Robert

Brodkey for their valuable suggestions and comments. I would like to thank Dr. Paula

Stevenson for her proofreading and many helps during the past five years. Thanks also

go to everyone who helped me in various ways, Paul Green, Leigh Evrard and Carl

Scott. I would like to thank previous and current colleagues in the polymer research

group.

In addition, Micro Metallics Corporation and Nova Chemical, Inc. donated post-

consumer and virgin polymers, Eastman Kodak Company loaned two molds, Dow

Chemical donated polypropylene, 3M Company donated Dynamar 9613, and GenCorp

Research donated a blender. The authors thank Professor Terry Gustafson and research

assistants Tony Frost and Kristin Frost of the Chemistry Department at The Ohio State

University for measuring the infrared and Raman vibrational spectra. The author thanks

Dr. John Clay for the measurement of the molecular weight, and Michael Ferry, Tu Tran,

vii

Sadu Prabowo, Andy Divine and Eric Mosser for help in measuring some physical

properties.

Finally, I would like to thank my parents for their continuing support through the

years of my study and my wife, Xia Cao, for her understanding, support, and

encouragement.

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VITA

September 25, 1967…………………………..………Born - Cixi, Zhejiang, P. R. China September 1985 - July 1989………………………….B.S. Chemical Engineering Zhejiang University Hangzhou, Zhejiang, P. R. China September 1989 - March 1992……………………….M.S. Chemical Engineering Zhejiang University Hangzhou, Zhejiang, P. R. China September 1998 – present….………………………...Graduate Research Associate

The Ohio State University Columbus, OH

PUBLICATIONS

1. Guojun Xu and Kurt Koelling, "Flow Marks/Tiger striping during Thin-Wall Injection Molding of Polypropylene", J. Injection Molding Technology (Submitted).

2. Jose L. Garcia, Kurt W. Koelling, Guojun Xu, and James W. Summers, “PVC Degradation During Injection Molding: Experimental Evaluation”, Journal of Vinyl & Additive Technology (In press).

3. Christiana Kuswanti, Guojun Xu, Jianhong Qiao, Julie Ann Stuart, Kurt Koelling, and Blaine Lilly, "An Engineering Approach to Plastics Reuse", Journal of Industrial Ecology, 6, 125-35, 2003.

4. Guojun Xu and Kurt Koelling, "Flow Marks during Injection Molding", ANTEC, Nashville, TN, 566-70, 2003.

5. Guojun Xu, Jianhong Qiao, Christiana Kuswanti, Kurt Koelling, Julie Ann Stuart, and Blaine Lilly, "Characterization of Virgin/Post-consumer Blended High Impact

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Polystyrene Resins for Injection Molding", J. of Applied Polymer Science, 84, 1-8, 2002.

6. Guojun Xu and Kurt Koelling, "Flow Marks during Injection Molding", ANTEC, San Francisco, CA, 521-5, 2002.

7. Guojun Xu and Kurt Koelling, "Study of Flow Marks during Thin-Wall Injection Molding", ANTEC, Dallas, TX, 604-7, 2001.

8. Guojun Xu, Jianhong Qiao, Christiana Kuswanti, Molly Simenz, Kurt Koelling, Julie Ann Stuart, and Blaine Lilly, "Insight into Reuse of High Impact Polystyrene from Post-Consumer Electronics Equipment Housing", IEEE International Symposium on Electronics and the Environment, San Francisco, CA, 348-53, 2000.

9. G. J. Xu, Y. M. Li, Z. Z. Hou, L. F. Feng and K. Wang, "Gas-Liquid Dispersion, Mixing and Heat Transfer in a Stirred Vessel", Can. J. of Chem. Eng., 75, 299-306, 1997.

10. Y. Li, G. Xu, M. Chen and K. Wang, "Slow Pelleting Coagulation of MBS Latex", Chem. Eng. Res. & Des., 75, 81-6, 1997.

11. Xu Guojun, Lianfang Feng, Yunming Li and Wang Kai, 'Pressure Drop of Pseuo-plastic Fluids in Static Mixers', Chinese J. of Chem. Eng. (English), 5(1), 93, 1997.

12. Y. M. Li, M. W. Chen, G. J. Xu, and K. Wang, "Continuous Slow Coagulation of Polymer Latex in Series Agitated Vessels", 36th IUPAC International Symposium on Macromolecules, IUPAC MACRO SEOUL'1996, Korea, 6-p01-01, 597, 1996.

13. Y. M. Li, G. J. Xu, M. W. Chen, S. H. Ou and K. Wang, "Slow Pelleting Coagulation of Polymer Latex Emulsion", 36th IUPAC International Symposium on Macromolecules, IUPAC MACRO SEOUL'1996, Korea, 6-p01-02, 598, 1996.

14. G. J. Xu, Y. M. Li and K. Wang, "Particle Growth Kinetics for Seed Coagulation of Polymer Latex", 36th IUPAC International Symposium on Macromolecules, IUPAC MACRO SEOUL'1996, Korea, 6-p01-03, 599, 1996.

15. Hou Zhizhong, Feng Lianfang, Li Yunming, Xu Guojun, Wang Kai and Pan Zuren, "Power Consumption of Agitation in a Gas-liquid System" (Chinese), 7th National Conference on Chemical Engineering, Beijing, China, B54, 424, 1994.

16. Hou zhizhong, Li Yunming, Feng Lianfang, Xu Guojun, Wang Kai and Pan Zuren, "Study on Heat Transfer of Gas-liquid System in an Agitated Vessel" (Chinese), 7th National Conference on Chemical Engineering, Beijing, China, B53, 420, 1994.

17. Hou Zhizhong, Wang Kai, Feng Lianfang, Li Yunming, Xu Guojun and Pan Zuren, "Fluid/Wall Heat Transfer in an Agitated Gas-Liquid Reactor" (English), International Workshop on the Advances in Chemical Engineering, Hangzhou, China, 1994.

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18. Guojun Xu, Lianfang Feng and Kai Wang, "Pressure Drop and Friction Factor for non-Newtonian Fluids in Static Mixers" (English), International Workshop on the Advances in Chemical Engineering, Hangzhou, China, 1994.

19. Hou Zhizhong, Feng Lianfang, Li Yunming, Xu Guojun and Wang Kai, "Gas-liquid Dispersion and Mixing Properties of Different Impellers in an Agitated Vessel", China Synthetic Rubber Industry (Chinese), 18(3), 147-50, 1995.

20. Hou Zhizhong, Li Yunming, Feng Lianfang, Xu Guojun and Wang Kai, "Properties of Gas-liquid Dispersion in a Baffle-gassed Multistage Agitated Vessel", China Synthetic Rubber Industry (Chinese), 18(4), 218-20, 1995.

21. Guojun Xu, Zhangmao Wang and Gantang Chen, "Study of Axial Diffusion Coefficients and Distinguish of Particulate/Aggregative Fluidization", Chemical Reaction Engineering and Technology (Chinese), 10(3), 306-10, 1994.

22. Guojun Xu, Zhangmao Wang and Gantang Chen, "A Model of Fluid Flow and Particle Circulation in a L/S Fluidized Bed", Chemical Reaction Engineering and Technology (Chinese), 11(3), 277-83, 1995.

23. Guojun Xu, "Fluidized Polymerization Reactors", China Synthetic Rubber Industry (Chinese), 18(1), 40-2, 1995.

24. Li Yunming, Xu Guojun, Ou Shuhui, Chen Miwen and Wang Kai, "Slow Coagulation of Polymer Latex" (Chinese), Annual Conference on Polymers, Guangzhou, 1179-80, 1995.

25. Zhizhong Hou, Lianfang Feng, Yunming Li, Guojun Xu and Kai Wang, "Heat Transfer Properties in Aerated Agitated Reactor", China Synthetic Rubber Industry (Chinese), 18(6), 338-40, 1995.

26. Yunming Li, Guojun Xu and Jingjing Xu, "A Study of Particle Growth in Seed Coagulation of Polymer Latex" (Chinese), Annual Conference on Polymer, Guangzhou, 1175-6, 1995.

27. Guojun Xu, Yunming Li and Jingjing Xu, "Methods of Seed Coagulation of Polymer Latex" (Chinese), Annual Conference on Polymer, Guangzhou, 1177-8, 1995.

28. Zhangmao Wang and Xu Guojun, "A Study Expansion and Axial Diffusion in a Liquid/Solid Spouted Fluidization Bed", Chemical Reaction Engineering and Technology (Chinese), 12(2), 184-8, 1996.

29. Guojun Xu, Lianfang Feng, Yuming Li, and Kai Wang, "A Study of Pressure drop for Pseudo-plastics Fluids in Kenics Mixers", China Synthetic Rubber Industry (Chinese), 19(2), 97-9, 1996.

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30. Deming Mao, Lianfang Feng, Guojun Xu and Kai Wang, "Effect on Control Volume and measured Points When the Beams Pass through Circular Media", Journal of Experimental Mechanics (Chinese), 11(1), 13-7, 1996.

31. Deming Mao, Lianfang Feng, Guojun Xu and Kai Wang, "Experimental Study on Agitator by LDA", Chem. Eng. J of Chinese University (Chinese), 10(3), 258-63, 1996.

32. Deming Mao, Lianfang Feng, Guojun Xu and Kai Wang, "Study of Spectral Analyses and Scales of Turbulence in Rushton Turbine", Chem. Eng. J of Chinese University (Chinese), 1996.

33. Yuming Li, Miwen Chen, Guojun Xu and Kai Wang, "Slow Pelleting Coagulation of Polymer Latex Emulsion", Chinese Chemical Letter (English), 7(3), 297-8, 1996.

FIELDS OF STUDY Major Field: Chemical Engineering Minor Field: Polymer Processing

Rheology

Chemical Reaction Engineering

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TABLE OF CONTENTS

Page

Abstract…………………………………………………………………………………..ii

Dedication………………………………………………………………………………...v

Acknowledgments……………………………………………………………………….vi

Vita……………………………………………………………………………………..viii

List of Tables……………….……………………………………………………….…..xv

List of Figures……………………………………………..…………………………..xvii

Chapters

1. Introduction...……………………………………………………………….…………1

2. Literature review.……………………………………………………………….……12

2.1 Flow marks.…………………………………………………………………12

2.1.1 Alternate flow marks………………………...……………...…….13

2.1.2 Synchronous flow marks……………………………………...…..19

2.2 Experiment with micro-features and improvement of simulation accuracy during thin-wall injection molding….………………………………..……..21

2.2.1 Thin-wall injection molding with micro-features…………..……..21

2.2.2 Cavity pressure and its prediction……………………………..…..34

2.3 Reuse of HIPS…………………………………………………..………...…37

3. Flow marks during thin-wall injection molding.……………………………………..45

3.1 Alternate dull and glossy flow marks….…………………………….……...45

3.1.1 Introduction………………………………………………………..45

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3.1.2 Experimental…………………………………………………….…47

3.1.3 Results and discussion…………………………………………….50

3.1.3.1 Rheological characterization…………………...……….50

3.1.3.2 Injection molding results……………………...…………51

3.1.3.3 Morphology and crystallinity…………………………....56

3.1.3.4 Extrusion…………………...……………………………57

3.1.3.5 Simulation………...……………………………………..57

3.1.3.6 Mechanism……………………...………………………59

3.1.4 Conclusion…………………...…...……………………………….64

3.2 Synchronous dull and glossy flow marks……………………………………65

3.2.1 Introduction………….……………………………………….…….65

3.2.2 Experimental………………………………………………………67

3.2.3 Results and discussion…………………………………….………69

3.2.3.1 Rheological characterization……………..……………...69

3.2.3.2 Injection molding results………………………………..69

3.2.3.3 Morphology and crystallinity…………………………....71

3.2.3.4 Extrusion…………………...……………………………72

3.2.3.5 Simulation……………...………………………………..72

3.2.3.6 Mechanism……………...……………………………….73

3.2.4 Conclusion………………..……………………………………….76

4. Experiment with micro-features and simulation accuracy improvement during thin-wall injection molding………………………………………………...…….……..126

4.1 Thin-wall injection molding with micro-features………………..………...126

4.1.1 Introduction..…………...…………..…………………….……...126

4.1.2 Experimental……………...………………………….….………127

4.1.3 Experimental results….………………………………….………129

4.1.4 Simulation results….……………………………………………..132

4.1.5 Conclusions……………...………………...…..………………...134

4.2 Cavity pressure and its prediction during thin wall injection molding……135

4.2.1 Introduction..…………...…………..……………………………135

xiv

4.2.2 Simulation………………...………………………….……….…137

4.2.3 Results and discussion.…………………………………………..140

4.2.4 Conclusions……………...………………...…..………………...145

5. Characterization of virgin/post-consumer blended high impact polystyrene resins for

injection molding………………………………………………………...…………190

5.1 Introduction..…………………………………………………….…….…..190

5.2 Experimental.………………………………………………………………193

5.2.1 Characterization of materials…………………………………….193

5.2.2 Measurement of molecular weight………………………………193

5.2.3 Microscopy and spectroscopy……………………………………194

5.2.4 Processing parameters for ASTM specimens…………………....195

5.2.5 Physical properties of ASTM specimens………………………...196

5.2.6 Application……………………………………………………….197

5.3 Results and discussions…..……………………………………………..…198

5.3.1 Characterization of materials…………………………………….198

5.3.2 Molecular weight……...……………………………….………...199

5.3.3 Microscopy and spectroscopy……………………………………199

5.3.4 Processing parameters for ASTM specimens……………………200

5.3.5 Physical properties of ASTM specimens………………………...200

5.3.6 Application………………………………………………………203

5.4 Conclusions...……………………………………………………………...204

6. Conclusions and future work……...………………………………………………..225

6.1 Flow marks………………...………………………………….…….……..225

6.2 Experiment with micro-features and simulation accuracy improvement.…226

6.3 Reuse of HIPS……………………………………………….…………….230

References…….……………………………………………………………………….231

xv

LIST OF TABLES

Table Page

3.1 Relaxation time and zero viscosity at 200°C…..………………………………..78

3.2 Viscosity-molecular weight……………..………………………….…………...79

3.3 Average roughness of the dull and shiny regions……..…………………….…..80

3.4 Average roughness of the dull and shiny regions……..…………………….…..81

4.1 Orthogonal array of the simulation…………………………………………….147

4.2 Coefficients of Cross-WLF equation…………………………………………..148

4.3 Relative influence of each factor on peak cavity pressure at different injection speeds at 230°C………………………………………………………………..149

4.4 Relative influence of each factor on peak cavity pressure at different injection speeds at 250°C………………………………………………………………..150

4.5 Relative influence of each factor on peak cavity pressure at different melt temperatures for HDPE at 0.5”/s………………………………………………151

4.6 Relative influence of each factor on maximum pressure drop at different injection speeds at 230°C………………………………………………………………..152

4.7 Relative influence of each factor on maximum pressure drop at different injection speeds at 250°C………………………………………………………………..153

4.8 Relative influence of each factor on maximum cavity pressure drop at different melt temperatures for HDPE at 0.5”/s………………………………………….154

xvi

5.1 Molecular weight and polydispersity…………………………………………..206

5.2 Weight percentage blends……………………………………………………..207

5.3 Mold design characteristics……………………………………………………208

5.4 Processing parameters from C-MOLD………………………………………...209

5.5 CMOLD parameters for film canister…………………………………………210

5.6 Tensile strength of film canisters……...…………………………………...…...211

xvii

LIST OF FIGURES

Figure Page

1.1 Difference between thin-wall and conventional injection molding.…..……………….7

1.2 Typical molding problems (1)...……………………………...…..……………….8

1.3 Typical molding problems (2)...……………………………...…..……………….9

1.4 Typical molding problems (3)..……………………………...…..……………....10

1.5 Environmentally conscious engineering system perspective...…..……………...11

2.1 Alternate and synchronous dull and glossy flow marks.…………………………43

2.2 Thin-wall plate with microstructures………………….…………………………44

3.1 Alternate dull and glossy regions.....……………………………………...….….82

3.2 Comparison of viscosity vs. frequency at 200°C.…………………………..…...83

3.3 Comparison of complex viscosity of PP-C at 180, 200, and 220°C.……………84

3.4 Comparison of elastic and viscous modulus at 200°C…………………………..85

3.5 First normal stress difference vs. shear rate at 200°C……………………..….…86

3.6 The first normal stress difference of PP-C vs. shear rate at 180, 200, and 220°C……………………………………………………………………………87

3.7 Transient extensional viscosity at 130°C……………………………………..…88

3.8 Determination of relation time by one-mode Giesekus model………….…..…..89

xviii

3.9 Flow marks of PP-C at different injection speeds……………………….……...90

3.10 A typical example of the alternate dull and shiny flow marks…………….……91

3.11 Effect of melt temperature on the wavelength λ………………………….…….92

3.12 Effect of mold temperature on the wavelength λ……………………………….93

3.13 The effect of mold thickness on the wavelength λ……………………………..94

3.14 Effect of melt temperature on the width of the flow marks…………………….95

3.15 Effect of mold temperature on the width of the flow marks……………………96

3.16 The effect of mold thickness on the width of the flow marks…………………..97

3.17 The starting of the flow marks, Vcri vs. melt temperature………………………98

3.18 Effect of melt temperature on the transition velocity, Vtrans…………………….99

3.19 Flow mark zone of PP-C………………………………………………………100

3.20 Morphology of surfaces of dull and shiny regions………………………….…101

3.21 Gross melt fracture of the PP in extrusion………………………………….…102

3.22 The wall shear stress versus apparent shear rate in the extrusion………….….103

3.23 Wall shear stress vs. percentage filled in the thin spiral mold…………….…..104

3.24 The critical wall shear stress at the middle of the gate at different melt temperatures…………………………………………………………………...105

3.25 The critical wall shear stress at the middle of the gate at different mold temperatures…………………………………………………………………...106

3.26 The similarity between extrusion and injection molding processes…………...107

3.27 Oscillating flow generates alternate flow marks………………………….…...108

3.28 Frequency of the flow marks versus flow front velocity………………………109

3.29 Synchronous dull and glossy regions………………………………………….110

3.30 Comparison of viscosity vs. frequency at 180°C……………………………...111

3.31 Comparison of Elastic and viscous modulus at 180°C…………………….….112

xix

3.32 First normal stress difference vs. shear rate at 180°C…………………………113

3.33 Extensional viscosity vs. time at 100°C……………………………………….114

3.34 Synchronous dull and shiny flow marks of HDPE2…………………………...115

3.35 Effect of melt temperature on wavelength…………………………………….116

3.36 Effect of mold temperature on wavelength……………………………………117

3.37 Effect of melt temperature on Vcri………………………………….…………118

3.38 Morphology of dull and shiny region of HDPE2……………………………...119

3.39 Flow curve of HDPE2 in extrusion……………………………………………120

3.40 Different extrudate irregularities at different wall shear stresses……………...121

3.41 Critical wall shear stress vs. percentage filled at different melt temperatures...122

3.42 Critical wall shear stress vs. percentage filled at different mold temperatures..123

3.43 Pulsating flow generates synchronous flow marks…………………………….124

3.44 Frequency of flow marks vs. Flow front velocity………………………………125

4.1 The long rectangular mold base with a disk-like insert………………………...155

4.2 The rectangular mold bases with a disk-like insert……………………………156

4.3 The disk-like mold insert which contains microchannels……………………..157

4.4 SEM picture of the a microchannel……………………………………………158

4.5 Dynamic viscosity of polypropylene…………………………………………..159

4.6 Dynamic viscosity of PMMA………………………………………………….160

4.7 SEM of a micro-channel……………………………………………………….161

4.8 Measured filling lengths in microchannels for PMMA in the long mold……..162

4.9 Measured filling lengths in microchannels for PP in the long mold…………..163

4.10 Measured filling lengths in microchannels for PMMA in the long mold……..164

4.11 Measured filling lengths in microchannels for PP in the long mold…………..165

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4.12 Measured filling lengths in microchannels for PP in the short mold…………..166

4.13 The cavity pressure profile in the long mold and the short mold……………...167

4.14 The filling length vs. Fourier number……………………….………………...168

4.15 The effect of packing stage on filling lengths..………………...……………...169

4.16 The effect of holding pressure on filling lengths..……………...……………...170

4.17 Comparison of the filling lengths between the simulation and experiment with constant heat transfer coefficients. Main flow heat transfer coefficient=25000 W/m2.K………………………………………………………………………...171

4.18 Comparison of the filling lengths between the simulation and experiment with constant heat transfer coefficients. Main flow heat transfer coefficient=2000 W/m2.K………………………………………………………………………...172

4.19 Comparison of the filling lengths between the simulation and experiment with variable heat transfer coefficient………………………………………………173

4.20 Schematic of the mold with thickness of 1 mm……………………………….174

4.21 Heat capacity of HDPE and PS………………………………………………..175

4.22 Specific volume of HDPE……………………………………………………..176

4.23 Specific volume of PS…………………………………………………………177

4.24 Experimental and fit viscosity vs. shear rate/ frequency for PS……………….178

4.25 Experimental and fit viscosity vs. shear rate/ frequency for HDPE…………...179

4.26 Comparison of cavity pressure with/without the effect of pressure on specific volume…………………………………………………………………………180

4.27 Comparison of cavity pressure with/without the effect of pressure on viscosity………………………………………………………………………..181

4.28 Comparison of cavity pressure with different heat transfer coefficients……....182

4.29 Comparison of cavity pressure with constant Cp and temperature-dependent Cp…………………………………………………………………………..….183

4.30 Comparison of cavity pressure with/without juncture loss………………….…184

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4.31 Pressure profiles right after the gate and at the end of the cavity at the injection speed of 76.2 mm/s and the melt temperature of 230 and 250°C…………...…185

4.32 Pressure profiles right after the gate at the melt temperature of 230°C with different injection speeds…………………………………………………...….186

4.33 Pressure profiles at the end of the cavity at the melt temperature of 230°C with different injection speeds……………………………………………………....187

4.34 Comparison of experimental and predicted pressure drop at the injection speed of 12.7 mm/s…………………………………………………………………..….188

4.35 Comparison of experimental and predicted pressure drop at the injection speed of 508 mm/s………………………………………………………………………..189

5.1 Film canister………………………………………...…………………..……...212

5.2 Comparison of the viscosity curves for post-consumer HIPS and virgin HIPS at 220°C……………………….…………………………….……………………213

5.3 Viscosity of Huntsman PS 702 blends with different percentages of post-consumer resin at about 200°C………………………….……………………..214

5.4 Viscosity of Nova PS 3350 blends with different percentages of post-consumer resin at about 200°C…………………………………………….……………..215

5.5 The images of different blends from ESEM (The length of the scales in the figures are 2 µm)………………………………………………………..…...….216

5.6 Raman spectroscopy of injection-molded post-consumer and Huntsman PS 702………………………………………………………………………...…...217

5.7 Infrared vibrational spectra of injection-molded post-consumer and Huntsman PS 702………………………………………………………………………….….218

5.8 Average Ra for six blends of Huntsman PS 702……………………………….219

5.9 Average Wa for six blends of Huntsman PS 702……………………………....220

5.10 Tensile strength and tensile modulus vs. weight percentage of virgin resin...…221

5.11 Flexural strength and flexural modulus vs. weight percentage of virgin resin...222

5.12 Impact strength and tensile modulus vs. weight percentage of virgin resin…...223

5.13 Meshing model of the film canister……………………………………………224

1

CHAPTER 1

INTRODUCTION

Among the large number of polymer processing operations, injection molding

has found the widest application for making articles which could be put to direct use.

Because of the superior manufacturability and the high degree of freedom of the form of

plastics products, injection molding is one of the most widely used processes for

processing plastics. In injection molding process, the polymer melt flows through a

runner system and gates to fill the mold cavity. When the filling is completed, more

melt is packed into the mold to compensate for volume shrinkage. The cooling stage

follows until the melt solidifies. Finally the part is ejected from the mold. Thin-wall

injection molding (TWIM) is conventionally defined as molding parts that have a

nominal wall thickness of 1 mm or less and a surface area of at least 50 cm2 [Whetten

and Belcher, 1994; Fasset, 1995]. Thin wall is relative, however. It also can be named

“thin-wall” as the flow length/thickness ratio is above 100 or 150 [Mahishi, 1998;

Maloney and Poslinski, 1998]. TWIM has been paid more and more attention,

2

especially in computer, communication and consumer electronic (3C) industries, due to

economic and environmental concerns. The reason is that thin-wall molded parts could

be made lighter, more compact, less expensive, and quicker because of fast cooling

[Smialek and Simpson, 1998]. New environmental regulations require less plastic to be

used at the source or in the initial stage of manufacturing [Miller, 1995]. Thus, TWIM is

a viable option for reducing the weight and size of plastic components.

The difference between conventional injection molding and TWIM is shown in

Fig. 1.1. The solidified “skin” layers are about 0.25 mm regardless of part thickness

[Fasset, 1995]. It means that the flow channel is very narrow and thus flow resistance is

very high in TWIM. Reducing flow resistance can be reached by increasing the melt or

mold temperature, reducing melt viscosity (increasing melt index), increasing injection

pressure, or injection speed [Fasset, 1995; Belcher and Hoenig, 1991]. However, high

melt temperature may cause degradation and increases cooling time which are

unacceptable. A rise in melt index shows a decrease in physical properties [Belcher and

Hoenig, 1991]. Therefore, high injection speed is preferred, and extremely high

injection pressure, 200-250 MPa (30,000-40,000 psi), is required [Colangelo and

Tremblay 1997]. Due to the thin part, cooling is fast. Thus the combination of the fast

cooling and high melt velocity (short fill time) significantly reduces the cycle time. The

typical cycle time of TWIM is 6-20 seconds while the cycle time for conventional

injection molding is 40-60 seconds [Selden, 2000]. The shrinkage is also low because of

the reduced part thickness [Delbarre, et al., 1991]. TWIM is characterized as high flow

rate, high pressure, high shear rate, high viscous heating, fast cooling and fast shrinkage.

3

However, TWIM has some disadvantages. Due to the rapid cooling of the

polymer melt, the operating window becomes narrower as the part becomes thinner

[Bozzelli, et al., 1997; Coxe, et al., 2000]. Specialized material is also required to

balance the trade-off between processability and physical properties [Cha and Lai, 2000],

which means material should both flow easily (high melt index) and retain good physical

properties. TWIM also makes design and process control more complicated. It is a big

challenge to fill the mold with a high flow length/thickness ratio at a high speed under

high pressure. For example, an additional accumulator is needed to maintain high

pressure at a short fill time. However, the operation of the accumulator affects the

molding stability [Chen, et al., 2000]. More robust control systems are required to

control the molding precisely and with a short response time [Selden, 2000; Hatch, et al.,

2001]. High injection pressure also needs high clamp tonnage which increases the

capital investment of equipment.

Processing, material, tooling, and machine interact with each other and greatly

affect the end results. For TWIM, systematic investigation about machine performance,

mold design/manufacture requirement, molding characteristics, computer aided

engineering (CAE) simulation, part quality and part design criteria is required [Chen, et

al., 2000]. However, the study is lacking due to the difficulty of thin-wall molding

process. Furthermore, the combination of viscoelastic materials, complex molding

geometry and cyclic processing conditions has generated some problems [Schmidt,

1998], such as flow marks, polymer degradation, high residual stress, sink marks and

warpage, under high-speed, high-pressure injection molding. So it is very important to

4

design, operate and control thin-wall molding optimally to guarantee part quality as well

as reduce cost. In this study, some issues, such as surface flow marks, thin-wall

injection molding with micro-features, mold cavity pressure and its prediction, and reuse

of post-consumer resin, are investigated.

Part appearance is one important criterion for assessing part quality because it

can be quickly evaluated. There are many aesthetic indictors that include warpage,

surface finish or gloss level, flash, sink marks, short shot, color, burns, bubbles,

transparency, pecks, scratching, stress marks, splay, drag, streaks, etc. [Salamon, et al.,

1998]. Some typical surface problems are shown in Figs. 1.2-1.4 [C-Mold design guide,

1998]. Flow marks are one of these problems created during injection molding. They

exhibit different levels of gloss on the surface of molded parts. These surface defects are

related to the melt flow and are thus called flow marks. They are also referred to as tiger

stripes, striping, halos, slip-stick, haze patterns, webs, chatter marks, blush or rings

[Salamon, et al., 1998; Dharia, 1999]. These flow marks occur especially on automotive

exterior parts and are very difficult to mask with paint. The defects limit the use of

many polymers in unpainted applications. In this study, two types of flow marks,

alternate dull and glossy and synchronous dull and glossy flow marks, are studied.

In recent years, the fabrication of polymer-based micro-components for optical

and biomedical applications has been paid more and more attention. The polymer

material is favored because of its low cost, good bio-compatibility, high optical clarity,

and high impact strength compared with silicon or glass. Micro-injection molding has

the potential for economical mass-production. It usually combines various lithography

5

techniques and injection molding [Weber and Ehrfeld, 1999]. Two types of micro-parts

are available: micro-sized parts whose delivery system including the runner and sprue is

much larger than the parts themselves and regular-sized parts with micro-features.

Micro-injection molding (MIM) is the injection molding of plastic parts with structure

dimensions in the micron or sub-micron range. The replication of the micro-features is

an important issue and it depends greatly on the size, aspect ratio and covered area

[Weber and Ehrfeld, 1999]. This study focuses on the thin-wall injection molding with

micro-features by experiment and numerical simulation. The filling lengths in

microchannels are simulated and compared with experimental results. Because the

predicted filling lengths in microchannels are very sensitive to the heat transfer

coefficients selected, it is necessary to study the effect of input property models on the

simulation outputs. We further study how the input properties affect the simulation

output in thin-wall injection molding. The output we choose is mold cavity pressure.

Injection mold cavity pressure is an important injection molding parameter. It is

regarded as a good indicator of molded part quality and injection machine control

performance. Cavity pressure not only indicates the material condition in the mold but

also affects the microstructure and part quality. Computer Aided Engineering (CAE) is a

common practice nowadays to help design, process, optimize, and troubleshoot thin-wall

injection molding processes. However, almost all users prefer better accuracy of CAE

simulation because large discrepancy between simulation and experiment may occur.

The difference may result from simplifying some important physical, thermal or other

properties, such as the pressure-dependent viscosity, variable heat transfer coefficient,

6

and variable material properties. The goal of the study is to understand how pressure-

dependent viscosity, heat capacity, heat transfer coefficient, juncture pressure loss and

pvT-data affect pressure prediction, and the importance of each parameter. Then

methods to improve the prediction accuracy will also be discussed.

As the increasing use of plastics, the plastics waste has become a main concern.

Environmentally conscious design and manufacturing is a strategic and competitive

practice. The reduction of material consumption is a big challenge for industrial

ecology. The attention paid to polymer recycling has increased in the past decade.

However, the life cycle trade-offs between collection, disposal, use of recycled plastics,

recyclability, reduction of process wastes, energy consumption, yields, and product

performance are complex, as shown in Fig. 1.5 [Stuart, 1999]. Life cycle assessment

and life cycle production planning models are very useful tools to analyze these

tradeoffs. However, resin degradation characteristics and potential design details are

required in order to apply these tools. Plastics recycling is important because more

efficient re-use of materials will reduce the quantities of plastics sent to landfills as well

as reduce raw material extraction. Waste prevention practices are increasingly

significant and are increasingly encouraged with the advent of take-back legislation

[Gamalski, 1996; Meffert and Kirchgeorg, 1997; Hubschman, et al., 1995]. In this

study, characterization and reuse of post-consumer resin (PCR) in a thin-wall application

is addressed.

7

Thin-Wall Part(1 mm)

Conventional Part(3 mm)

Solid Skin 0.25 mmSolid Skin 0.25 mm

Flowing Core 2.5 mmFlowing Core 0.5 mm

Fig. 1.1. Difference between thin-wall and conventional injection molding.

8

Black specks black streaks

Brittleness Burn marks

Delamination Dimensional variation

Flash Flow marks

Fig. 1.2. Typical molding problems (1) [C-Mold design guide, 1998].

9

Hesitation

Jetting

Ripples Silver streaks

Fig. 1.3. Typical molding problems (2) [C-Mold design guide, 1998].

10

Fish eyes

Sink marks

Weld lines or Meld lines

Fig. 1.4. Typical molding problems (3) [C-Mold design guide, 1998].

11

Raw Materials

Concurrent Product, Process& System Design forAssembly/Reuse/End-of-Use

Energy

Disposal

Distribution

Consumer

Manufacturing/Services

Repair

Rework

Recycling

Downcycling

Reusable MaterialContent Model

Degradation Model

VirginMaterials

Fig. 1.5. Environmentally conscious engineering system perspective [Stuart, 1999].

12

CHAPTER 2

LITERATURE REVIEW

2.1 FLOW MARKS

The application of injection molding has greatly increased in recent years.

However, there is a conflict between the high quality of exterior appearance and short

cycle time. Injection molding sometimes creates several kinds of surface defects during

processing, differing levels of gloss on the surface of molded parts. The surface defects

are related to the melt flow and are thus called flow marks. They are also referred to as

tiger stripes, striping, halos, slip-stick, haze patterns, webs, chatter marks, blush or rings

[Salamon, et al., 1998; Dharia, 1999]. These matte areas occur on one or both sides of

parts. When they occur on both sides, those on one side of the parts are in phase or out

of phase with those on the other side of the parts. According to Yokoi [1994a], three

kinds of flow marks are classified according to the surface conditions of flow marks.

They are (1) micro-grooved zones like LP records, (2) synchronous dull and glossy

surfaces and (3) alternate dull and glossy surfaces. The kind of flow mark with micro-

grooved zones like LP records is also well known as wave-like flow marks. Flow marks

13

may occur on center-gated parts made with multi-phase polymer systems, including

rubber modified polymers, thermoplatic olefin (TPO), blends (HIPS, PC/ABS),

copolymer (ASA, ABS, EP), and semi-crystalline polymers (LDPE, HDPE, PP/Talc).

They may also occur on edge-gated parts [Salamon, et al., 1998].

Here we discuss two types of these surface defects: those associated with the

flow instability and those associated with the change of flow front velocity [Salamon, et

al., 1998]. One type of flow mark is characterized as alternate dull and glossy surfaces

where flow marks on one side are out of phase with those on the other side of the part, as

shown in Fig. 2.1(a). Another type of flow mark is characterized as repeated dull and

glossy regions where a dull/glossy zone on one side corresponds to a dull/glossy zone on

the other side, as shown in Fig. 2.1(b). These flow marks cause surface defects that

occur especially on automotive exterior parts. Flow marks can be very difficult to mask

with paint due to the change in porous structure of dull and shiny regions. The defects

also limit the use of many polymers in unpainted applications.

2.1.1 Alternate Flow Marks (AFM)

One type of flow mark is characterized as alternate dull and glossy surfaces

[Yokoi, 1994a]. Flow marks were observed as early as in 1961 and some work has been

done to explain and eliminate them [Yokoi, 1994b; Chang, 1996a; Chang, 1996b;

Hobbs, 1996; Heuzey, et al., 1997; Hamada and Tsunasawa, 1996; Dharia, 1999; Bulters

and Schepens, 2000; Grillet, et al., 2000; Charmeau, et al., 2000; Xu and Koelling, 2001;

Jayaraman, et al., 2002]. In the literature, the effect of operating variables, physical

14

properties of plastics, and mold geometry has been discussed. Operating variables

include injection speed, injection pressure, melt temperature, and mold temperature. The

physical properties cover different kinds of polymers, the rheology of polymer melt and

molecular weight distribution, while the mold geometry includes gates, mold thickness

and different molds. Moreover, several kinds of mechanisms have been proposed to

explain the generation of flow marks. However, little has truly been understood on why

flow marks occur and how to predict and eliminate them. Furthermore, the results in

literature sometimes conflict with one another.

Alternate flow marks were typically observed in LDPE and PP/talc and were

caused by a cyclic unsymmetrical flow front [Yokoi, 1994b]. There seemed to be a clear

correlation between the shear stress level on the cavity wall and the flow mark

generation region, and thus the flow marks were thought to occur due to the melt fracture

on the cavity surface. The flow marks may involve wall slip, though the author did not

state this. Chang used a slip mechanism to explain the surface defects [Chang, 1996a;

Chang, 1996b]. When ASA polymer melt flow meets a thickness change from gate to

cavity, slip can occur if the melt has low adhesion (friction) to the mold surface due to a

low die swell. The slip can initiate a melt flow instability. Thus, this kind of flow

instability causes flow marks with alternate dull and glossy regions. It was shown that

recoverable shear strain, shear stress and the coefficient of friction between the melt and

mold were key controlling factors for the generation of flow marks. It was also found

that the higher the ratio of step size, the more severe the degree of flow marks.

15

In a study of several blends of BPA polycarbonate and ABS resins, Hobbs found

that at higher injection rates, the flow marks were more continuous and pronounced

[Hobbs, 1996]. The study indicated that stick/slip flow at high wall shear stresses

created the flow marks and wall slip was worsened by lower friction coefficients. It was

found that wall slip first occurred on one face of the mold. When the melt front flow

chattered across the surface, high frequency ripples developed. This kind of slip

generated a distortion in the velocity gradient across the flow channel and caused the

flow front to oscillate back and forth. The flow marks were formed by dragging the

partially solidified melt across the mold surface.

It was hypothesized that wall slip is associated with some kinds of flow marks.

However, Heuzey, et al. found no obvious relationship between the wall slip and flow

marks [Heuzey, et al., 1997]. Using linear polyethylene, they found that one of the

resins did not slip in capillary flow experiments. Furthermore, coating on a mold wall

did not affect the occurrence of flow marks. They concluded that wall slip does not

affect the occurrence of the flow marks. They believed that three main factors were

involved in the occurrence of alternate dull and glossy flow marks: the surface cohesive

strength of the semi-solidified polymer, the adhesion between the solid layer and the

mold, and the high shear stress in the melt near the wall. The generation of flow marks

was due to the filamentation and stretching of semi-solidified materials.

In the thin-wall injection molding experiment, flow marks with alternate dull and

glossy regions were studied using PC and ABS blend [Hamada and Tsunasawa, 1996].

It was found that when no flow marks occurred, PC and ABS flowed in steady, laminar

16

motion with a normal fountain flow and in layers due to its low viscosity. However,

when flow marks occurred, the PC and ABS flowed with oscillation. So, the center of

the flow moved in the direction of the mold thickness. This kind of abnormal fountain

flow happened because of the high viscosity of resin flow. Under this condition, high

shear stress is applied on the PC and ABS. The result was that the PC phase at the tip of

the flow front might be broken and then PC and ABS coexisted, causing cloudy (dull)

regions.

In a study of binary blends of polypropylene and ethylene co or ter-polymers

[Dharia, 1999], it was concluded that the increase in built-in stress between the skin and

core at the melt front increased surface defects. The study showed that the tendency was

the combined effect of rapid stress build-up and slow recovery. It was also found that

flow marks were caused by a melt flow instability and the inability of melt to recover

from the stress change at the flow front. More recently, Bulters and Schepens visualized

the mold filling process by a layered block of PP with contrasted colors. It was found

that the flow front was unstable and the black layer broke through at the surface. They

claimed that flow marks resulted from a flow front instability [Bulters and Schepens,

2000]. Furthermore, Grillet, et al. conducted a finite element simulation for a very strain

hardening fluid and a very strain softening fluid. After the steady numerical

calculations, a linear stability analysis was performed and it was found that the most

unstable eigenvector was an oscillatory, swirling flow near the stagnation point at the

free surface [Grillet, et al., 2000]. Alternate flow marks of TPO blends were studied by

Jayaraman, et al. [2002]. The disperse phase morphology was analyzed in detail. It was

17

found that the rubber particles in the out of the flow mark region were highly stretched

and had a high aspect ratio, while the rubber particles in the flow mark region were less

stretched and had a low aspect ratio. It was concluded that the flow marks occurred in

the long spans of the unbalanced flow front.

The effect of mold geometry and processing variables was studied by Chang

[Chang, 1996b]. It was found that the mold thickness and mold surface temperature

were the controlling factors on flow marks. It was also found that a larger thickness

ratio caused more severe flow marks, and an increase in mold temperature decreased the

rank of defect severity. Though the increase of injection speed and pressure worsened

the flow marks, their effects were not as important as the above two factors. When

rubber levels decreased, surface appearance improved because of the combination of the

effect of recoverable shear strain and shear stress. As for the effect of carbon black

loading, surface defect severity increased with the increase of carbon black levels.

Chang concluded that the higher the melt elasticity, the better the surface appearance.

However, the surface appearance was improved by increasing the coefficient of friction

or decreasing the lubricant level.

Hobbs found that with the increase of the injection speed, the flow marks were

more continuous and pronounced [Hobbs, 1996]. The trend of the results is consistent

with Chang’s work [1996b]. High surface roughness values of compound lowered the

coefficient of sliding friction, increased stick/slip flow, and thus reduced gloss value.

In the injection molding for processing LLDPE and HDPE, flow marks with

alternate dull and glossy regions were formed [Heuzey, et al., 1997]. It was found that

18

the flow marks were affected by mold surface finish. In their experiment, injection rate

was the most important factor affecting the flow marks. The severity of flow marks

increased with the increase of the injection rate. It is consistent with Chang’s [1996a;

1996b) and Hobbs’ [1996] results. However, wall slip did not lead to in the generation

of flow marks. It was found that coating had no great effect on flow marks. However,

surface defects were amplified by adding silicone oil. It was also found that mold

thickness had a small effect on flow marks, but the observation was different from that

of Chang's work [Chang, 1996b].

In the thin-wall injection mold, flow marks were generated when processing a

PC/ABS blend [Hamada and Tsunasawa, 1996]. It was found that low cylinder

temperature, low mold cavity temperature and high injection speed were the factors

generating flow marks. The gate design was also found to be important.

Dharia found that the most important factor producing flow marks was lower

mold temperature [Dharia, 1999]. The second important factor was injection pressure,

while the third important factor was injection speed. It was found that the high injection

speed generated more pronounced flow marks. In all cases, even moderate backpressure

could reduce flow marks.

Although experimental evidences show that oscillating instability occurred in

mold filling [Chang, 1996a; Hamada and Tsunasawa, 1996; Bulters and Schepens,

2000], there is disagreement on why the instabilities occur and where it originates.

Furthermore, it is widely known that elastic instabilities occur upstream of a contraction,

such as a capillary die or slit die, in extrusion or spinning. [Piau, et al., 1988; White, et

19

al., 1987; Boger and Walters, 1993; Koelling and Prud’homme, 1991]. However, the

researchers studying the flow marks have not studied the entry instability and its

relationship to the flow marks, although Dharia already noticed the similarity between

extrusion and injection molding processes [Dharia, 1999].

In this study, we investigate the effect of operating parameters and different

polymer melts on the wavelength, width, and gloss variation of the flow marks. Then

several methods to reduce the flow marks are discussed. We study the correlation

between gross melt fracture in extrusion and alternate dull and glossy flow marks in

injection molding. Then, an entry viscoelastic flow instability mechanism is proposed to

explain the alternate flow marks.

2.1.2 Synchronous Flow Marks (AFM)

Although alternate dull and shiny flow marks and wavelike flow marks have

been studied in the literature [Tredoux and Satoh, 1999; Tredoux, et al., 2000; Yokoi, et

al., 1994a; Yoshii, et al., 1993; Yoshii, et al., 1996; Lee and Mills, 1994], little attention

has been given to synchronous flow marks [Yokoi, et al., 1994c; Salamon, et al., 1998].

The synchronous dull and glossy flow marks usually occur in high viscosity PP with a

narrow gate [Yokoi, et al., 1994c]. A glass-inserted mold was used to visualize the flow

front during the mold filling process, and homopolymer PP was used in their experiment.

It was observed that synchronous dull and glossy flow marks were generated, but no

flow marks were observed on the glass surface or polished cavity surface. It was found

that at high injection rates, many thin and narrow flow marks occurred [Yokoi, et al.,

20

1994c]. The gate shapes greatly affected the generation of flow marks and the flow

marks varied dramatically with the front flow velocity. At higher melt temperature, flow

marks became thinner. At the melt temperature of 240ºC, flow marks did not show up

where the variation of gate pressure and flow front velocity was small. They explained

that near the gate, the flow resistance was high causing the flow quantity to decrease.

The gate pressure was increased during the filling, while the melt velocity was decreased

at the flow front and the melt was cooled down. On the other hand, the gate was frozen

and the flow resistance was increased. Therefore, the melt at the flow front was

accelerated with the release of the high gate pressure. At that moment, the resin near the

flow front underwent cooling, so the transcription precision decreased in the subsequent

fountain flow process. Then the flow marks were formed.

In the injection molding of HIPS in a rectangular mold with a center-gate, halos

similar to flow marks with synchronous dull and glossy regions were formed [Salamon,

et al., 1998]. It was found that the temperature gradient between any two zones was the

cause of the formation of the halos. It was also proposed that the temperature gradient

must decrease in the direction of the flow in order to form the halo and the halo could be

reduced by a design that minimizes the heat losses to reduce the temperature gradient. It

was also shown that the mold temperature was significant in controlling the halo. When

the mold temperature was high enough, the halo did not occur because the surface

stresses relaxed and recovered. However, the halo always appeared when the mold

temperature was set below the annealing temperature. With the increase of injection

rates, the halos became more prominent and the diameter of the halos became larger

21

because the thickness of the skin layer was reduced. It was also found that the part

surface was rougher in the halo region, and the valleys in the halo region were aligned

with the flow direction. They proposed that the stress was rapidly decreased for the

polymer melt from a colder zone to a hotter zone, causing rapid reduction of strain rate.

This reduction of strain rate therefore increased the size of the melt and the melt must

wrinkle or fold to respond to this increase because the melt was confined in the mold

cavity. The wrinkles or folds were aligned with the flow direction and quickly solidified

without relaxation when contacting the cold mold surface, causing flow marks to form.

This study considers the effect of operating parameters and mold surface coatings

on flow marks of different polymer melts. A possible correlation between gross melt

fracture in extrusion and synchronous dull and glossy flow marks in injection molding is

discussed. Finally, a possible mechanism is proposed.

2.2 EXPERIMENTS WITH MICRO-FEATURES AND IMPROVEMENT OF

SIMULATION ACCURACY DURING THIN-WALL INJECTION MOLDING

2.2.1 Thin-Wall Injection Molding with Micro-Features

In recent years, the fabrication of polymer-based micro-components for optical

and biomedical applications has been paid more and more attention. The polymer

material is favored because of its low cost, good bio-compatibility, high optical clarity,

and high impact strength compared with silicon or glass. Micro-injection molding has

the potential for economical mass-production. It usually combines various lithography

techniques and injection molding [Weber and Ehrfeld, 1999]. Two types of micro-parts

22

are available: micro-sized parts and regular-sized parts with micro-features. Micro-

injection molding (MIM) is the injection molding of plastic parts with structure

dimensions in the micron or sub-micron range. Micro-injection molding process meets

the requirement of cost-effective replication in large scale series. Different small or

micro components with the following specifications can be injection molded

[Hanemann, et al., 1997a]:

• Plate-shaped microparts with microstructures of any lateral form.

• Volume of the standard substrate base plate: 20×60×2 mm3 (width×length×height).

• Microstructure height up to 1.6 mm.

• Smallest wall thickness down to 30 µm.

• Smallest structure detail 0.2 µm.

• Aspect ratio up to 30:1.

• Suitable materials: PMMA, PC, PSU, POM, PA12, PEEK, etc.

Usually, micro structured mold inserts are made by special processes and then

attached to standard molds [Piotter, et al., 1997]. The critical dimensions which can be

produced by micro-injection molding in good shape are mainly determined by aspect

ratios. Common microstructured products such as CDs and DVDs could not be

compared with LIGA microstructures with aspect ratios of ten to 600 [Piotter, 1997].

Modification of the molding machinery, the tool’s construction, and the molding

operation is demanded to injection molding of microstructures with high aspect ratios.

23

The main difference between thin-wall injection molding and micro-injection

molding is described in detail as follows:

a. Mold Technology

For thin-wall injection molding, high speeds and high pressures can make mold

plates flex. It may cause flash or thicker wall sections of molded parts. Thus thick and

strong molds are required in thin-wall injection molding to resist high pressure. TWIM

also requires relatively large and/or multi gates for easier mold filling. More ejection

pins are needed because parts are tightly packed. Larger ejection pins are used to avoid

part distortion. Sometimes vacuum evacuation is recommended to minimize weld lines

and possible burning of compressed gas [Fasset, 1995]. However, usually venting along

the parting line combining the venting of ejectors and core pins can solve this problem.

In injection molding of microstructures, micro structured mold inserts are made

and then attached to standard molds. The mold cavity can be prepared by LIGA process

or more traditional processes such as micro-turning, micro-sparking and laser-erosion

[Piotter, et al., 1997]. LIGA process is a relatively new process to produce molds or

cavities. Typically, micro mold inserts have high aspect ratios, especially from LIGA

process. Parallel plane walls and lacking of injector slope make demolding difficult.

However, multi-stepped master structures can be produced by inclined x-ray exposure,

two-stepped resist structures, or the combination of several microstructuring techniques

[Piotter, et al., 1997]. These techniques generate pretty smooth surface (roughness is

smaller than 10 nm). Molds must meet high demand, such as accuracy requirement.

24

Because conventional venting through parting planes or gaps is impossible for

microstructures due to the “blind holes” in microstructures [Hanemann, et al., 1997a],

venting is a problem. Compressed hot air may burn the polymer, so compressed air must

be evacuated by a vacuum pump. The mold inserts should be carried out certain number

of shots in practice. To avoid damage, it is wise to reduce stress on the mold insert. The

variothermal heating is a good choice in this point because high temperature lowers

viscosity and makes the mold inserts easy to be filled. Reducing injection pressure or

holding pressure is a choice. Wear is another problem. It is reported that wear did not

occur after 1000 shots for LIGA mood inserts made from nickel or nickel-cobalt [Piotter,

et al., 1997].

b. Machine Technology

For thin-wall injection molding, high injection speed, 500 mm/s, is preferred and

extremely high injection pressure, 200-250 MPa, is required [Colangelo and Tremblay,

1997]. The purpose is to reduce flow resistance caused by narrow flow channels. High

clamping force is also required because of high pressure. High clamp tonnage means

high capital investment of equipment. Due to the thin part, cooling is fast. Thus the

combination of the fast cooling and high melt velocity significantly reduces the cycle

time. Precise control is required to get good surface finishing. TWIM also makes

design and process control more complicated. It is a big challenge to fill the mold with a

high flow length/thickness ratio at a high speed under high pressure. For example, an

accumulator is needed to maintain a high pressure at a short fill time. More robust

25

control system is required to control the molding precisely within a short response time

[Selden, 2000].

Development of micro-injection technology started in early 1980’s. No

appropriate injection molding machine was available at that time and people had to

modify the commercial hydraulic driven units with a low clamping force. To mold

microstructures, people usually use a small screw in a conventional screw-injection

molding machine. However, the screw is easy to be broken under shear. To reduce the

shot size suitable for microstructures, people adopt properly sized runner systems or

directly inject melt into cavities using a hot runner nozzle without runner systems

[Rogalla and Michaeli, 1997]. Brand new injection molding machine for

microstructures was under development in middle 1990’s. The machine developed at

FZK can inject very small amount of resin, for example 0.025g, with a stable process

[Piotter, et al., 2001]. The machine for micro-injection molding includes venting and

variothermal heating systems. In contrast to thin-wall injection, high injection pressure

and speed are not essential. Of course, injection pressure and speed as well as other

parameters influence the part quality and dimension stability, which is also true for thin-

wall injection molding.

Incomplete filling is a main concern in micro-injection molding. People use a

variety of reaction injection methods to reduce viscosity. The common method is using

photoinduced polymerization of MMA/PMMA based resins. The molding can be

conducted at ambient temperature using a machine with a small sized powerful UV light

26

source. The polymerization time of 2.5 minutes could be obtained [Hanemann, et al.,

1997a]. Thermally initiated RIM is another technique. A relatively simply and reliable

mold filling and good accuracy could be obtained because of the low viscosity of the cast

resin. Resins based on acrylates, methacrylates, amides and silicones are thermally

curable. However, this technique needs elevated temperature to start polymerization.

The process is relatively slow and also needs mixing and metering units.

c. Material

For thin-wall injection molding, the material should flow easily, have enough

impact strength and high stiffness and resist polymer degradation due to shear heating.

However, good flowing ability (high melt index) usually means low physical properties.

So, specialized material is required to balance the trade-off between processability and

physical properties. Some suitable materials especially for thin-wall injection have been

developed. Appropriate materials for micro-injection molding must have low viscosity

but satisfactory mechanical properties. Common materials used are PMMA, PC, PSU,

POM, PA12, PEEK, etc.

d. Operating

In thin-wall injection molding, the pressure and velocity are very high. TWIM

prefers low viscosity and it mainly relies on high shear rate instead of high temperature.

The mold temperature usually is low in order to accelerate heat transfer and reduce

cooling time. Due to the rapid cooling of polymer melt, the operating window is

narrower as the part becomes thinner.

27

Common injection molding parameters such as relatively low mold temperature

and injection pressure will cause incomplete filling of mold inserts. In order to fill the

mold inserts completely, the temperature on the surface of mold inserts is usually heated

up to melt temperature. This is so-called variothermal heating. Usually the temperature

is above glass transition point for semi-crystalline polymers and near melting point for

crystalline polymers to reduce flow resistance. The mold is completely filled just before

the ejection because conventional venting method is impossible for microstructures.

However, it will inevitably increase the cycle time if using a variothermal process. The

shortest cycle time reported is 70 s with aspect ratio of only 2.5 and microstructures with

high aspect ratios needs more than 6 minutes [Piotter, et al., 1997], which is much longer

than thin wall injection molding.

It should be noted that for most microstructures with low aspect ratios (<2),

usually a constant temperature is used but the temperature is higher than that in

conventional injection molding.

e. Simulation

The modeling of micro-injection molding is different from conventional or thin-

wall injection molding process. Several models have been developed during last

decades to simulate the filling of conventional injection molding. Most injection molded

parts are complex, the filling process is non-isothermal, and polymer fluids demonstrate

non-Newtonian behavior. So, it is very difficult to simulate the filling process without

simplification. The pioneering work focused on pressure and temperature prediction of

28

simple geometries. Usually, a generalized Hele-Shaw flow model is used to simplify the

governing equations for non-isothermal, non-Newtonian melt flows. In most cases, the

simplification successfully predicts the modability (pressure and velocity fields, air

entrapment, temperature distribution and stress concentration regions) [Hetu, et al.,

1998].

The Hele-Shaw approximation neglects flow in the gapwise direction [Garcia , et

al., 1991]. So, the velocity in the thickness direction w=0.

Continuity equation:

0=⋅∇ u

Momentum equation:

0)( =⋅∇+∇ uP σ

))(()(2)( Ti uu ∇+∇== ηηγµησ &

The Hele-Shaw approximation can be written as

0=∇⋅∇ PS i.e. 0)()( =∂∂

∂∂+

∂∂

∂∂

y

PS

yx

PS

x

where ∫=H

dzz

S0

2

)(η

Because the heat conduction in flow direction can be neglected, energy equation can

expressed as:

Φ+∂∂

∂∂=

∂∂+

∂∂+

∂∂

))(()(z

Tk

zy

Tv

x

Tu

t

TC pρ

where Φ is viscous heating.

29

Boundary conditions:

Injection gates:

Q=Q(t) or P=P(t)

T=Tmelt

Moving flow fronts:

P=0

T=Tcore

Mold wall:

0=⋅ nu

T=Tmold or q=h(Tw-T)

It should be noted that the no-slip does not hold anymore after the Hele-Shaw

approximation.

However, these models are limited in the scope of the information that they can

generate. Furthermore, the Hele-Shaw approximation can not accurately predict the

fluid behavior at flow front and the flow behavior near or at solid walls, the phenomenon

occurring at the merging of two or more streams (weld lines), and the kinematics in

gates, ribs, or sudden thickness change, the areas where shear and extensional

deformations contribute significantly to the stress field [Gao, et al., 1998]. A three-

dimensional simulation could provide complementary and more detailed information.

However, because of its intensive computation nature, 3D simulation started only several

years ago [Han and Gupta, 1999]. The difficulties met in simulating 3-D filling are

[Gao, et al., 1998]:

30

• The computational domain is usually a 3D volume having a complex shape.

• The free surface is subject to large deformations and multiple interfaces may

come in contact with each other.

• The prediction of the flow boundary layers requires no-slip boundary condition.

The equations of continuity, momentum and energy can be expressed as [Chang and

Yang, 2001]:

0=⋅∇+∂∂

ut

ρρ

gPuuut

ρσρρ +−∇=−⋅∇+∂∂

)()(

))(( Tuu ∇+∇= ησ

2)()( γηρ &+∇∇=∇⋅+∂∂

TkTut

TC p

The boundary conditions [Gao, et al., 1998]:

meltTTuu == ;0 at Γinlet

tnPnu =−⋅)(σ on Γtractions

moldTTu == ;0 or q=h(Tw-T) on Γwall

The tracking of the evolution of melt front is usually modeled by pseudo-concentration

method:

0)( =⋅∇+∂∂

fut

f

31

where f=0 is defined air phase, and f=1 as melt phase. The inertia term and body force

term in momentum equation and viscous heating in energy equation can be neglected

sometimes [Gao, et al., 1998].

For thin-wall injection molding, the Hele-Shaw approximation is usually used

and it generally provides good results. However, the results are not perfect and error is

large in some cases, as discussed above. Furthermore, due to the characteristic of thin-

wall injection molding, the main reason of unsatisfied results is due to the inaccurate

description of polymer physical properties in the unstable process. Because of extremely

high pressure, the effect of pressure on compressibility and viscosity should be

considered. Because the typical filling time is 0.2 s in thin-wall injection molding, the

temperature changes dramatically. The isothermal condition combining with high

pressure make it very difficulty to describe the heat conductivity, heat capacity,

especially heat transfer coefficient. Study showed that neglecting the effect of pressure

on viscosity may cause large error in predicting cavity pressure. The heat conductivity

and heat capacity used are often measured at constant temperature and low pressure. So,

the main effort to improve the prediction accuracy focuses on the improvement of the

property description, which will be discussed in detail in Section 2.2.2.

Simulation of micro-injection molding is a new area and very little work has

been done. For flat and thin parts, so-called standard injection molding parts, 22

1D

codes usually provide good results. However, difficulty occurs when simulating the

filling of microstructures with high aspect ratios [Piotter, et al., 1997; Hanemann, et al.,

32

1997b; Yu, et al., 2001]. Although the simplification by assuming thin and flat parts

makes calculation easy and fast, the dimensional character of microstructures is not thin

and flat anymore. The examples are micro parts like micro gearwheels, micro sensors,

etc. It is expected that the simplification does not hold anymore and proper 3D

simulation is necessary. For the parts with microstructures, such as LabCD, they show

thin-wall plates with microstructures, as shown in Fig. 2.2. Hele-Shaw approximation

gives the average information in gapwise direction in the large thin plate. Obviously,

local information of T, P and v at inlet of the micro-channel is crucial for the simulation

of the flow in the micro-channel. So, it will cause big discrepancy in simulating the

microstructures. Furthermore, viscosity and surface tension are even more important for

microstructures. The surface roughness may also play a significant role in

microstructures. Moreover, the material data, especially rheology data for macroscopic

application should be re-examed when applied to micro scale. Previous study showed

that 22

1D simulation such as C-MOLD is not sufficient to describe all molding effects

anymore for extremely small structures of microparts [Hanemann, et al., 1997b].

Modifications to most conventional programs such as MOLDFLOW and

CADMOOULD-SD or new 3-D transient codes are required in order to simulate the

filling of micro-injection molding [Hanemann, et al., 1997b]. For the thin part with

microstructures such as LabCD, the modification can be as follow: Using 2D codes to

simulate the flow in the large domain while using 3D to simulate the flow in the

microstructures [Hanemann, et al., 1997b].

33

In this study of the thin-wall molding of base plate with microchannels, the

velocity variation in the width direction y is negligible, a 2D x-z plane simulation is

used. The momentum equations, the continuity equation and the energy equation are

written as follows at a quasi-steady state [Yu, et al., 2004a]:

0)( =⋅∇ vρ

x

puu

∂∂−=∇⋅∇−⋅∇ )()( ηρv

z

pvv

∂∂−=∇⋅∇−⋅∇ )()( ηρv

HTkTCTCt pp +∇⋅∇=⋅∇+

∂∂

)()()( vρρ

where ⎥⎥⎦

⎤

⎢⎢⎣

⎡⎟⎠

⎞⎜⎝

⎛

∂∂+

∂∂+⎟

⎠

⎞⎜⎝

⎛

∂∂+⎟

⎠

⎞⎜⎝

⎛

∂∂=

222

22x

v

z

u

z

v

x

uH η

In this study, thin-wall injection molding with micro-features was studied

experimentally and numerically. The filling lengths in microchannels are simulated and

compared with experimental results. Because the predicted degree of filling in

microchannels are very sensitive to the heat transfer coefficients selected, it is important

to study the effect of selection of property models on simulation outputs. We then

further study how the input properties generally affect the output in thin-wall simulation.

The output we choose is mold cavity pressure.

34

2.2.2 Cavity Pressure and its Prediction

Injection mold cavity pressure is one of the most important parameters in thin-

wall injection molding. It is regarded as a good indicator of molded part quality and

injection machine control performance [Angstadt, 2001; Dubay, 2001]. It not only

indicates the material condition in the mold but also affects the microstructure and part

quality [Macfarlane and Dubay, 2000; Gao, et al., 1996; Gao, et al., 1996]. Cavity

pressure can affect part weight, dimensions, cosmetics, gloss, warpage, shrinkage, etc.

[Bozzelli and Cardinal, 1996]. It is therefore very useful to study the effect of injection

operating variables and material properties on cavity pressure (gradient). Usually, low

cavity pressure is preferred because low pressure demands low injection capacity that

reduces equipment cost, reduces shear orientation, and produces low shear stress which

is essential to avoid quality problems such as warpage and low mechanical properties.

Low stress is even more important in stereolithography [Dell’Arciprete, et al., 1999;

Palmer and Colton, 2000] or micro-injection molding [Yu, et al., 2001] where mold

wear and durability are main concerns.

Today it is common to use computer aided engineering (CAE) programs to

successfully design a part. CAE can be used to troubleshoot and solve problems

concerning filling time, injection pressure, gate location and dimension, warpage,

coolant efficiency, etc. [Kalnin and Zluhan, 1999]. The application of CAE has the

potential to reduce overall production cost and improve part quality. Using CAE to

35

analyze part quality has given encouraging results and it is possible to design a good

mold without any tool tryouts [Kansal, 2000].

However, almost all users would prefer better accuracy of CAE simulation

[Ainoya and Amono, 2001]. During thin-wall injection molding (TWIM), the error of

the prediction of cavity pressure from CAE simulation can vary from 50% to more than

100%, and the error increases as the parts become thinner [Chen, et al., 2000]. The

discrepancy may result from neglecting some important factors during simulation. For

example, the effect of pressure on viscosity is important because of very high pressure

which occurs in TWIM [Chen, et al., 2000; Amano and Ainoya, 2000; Fasset, 1995;

Mahishi, 1998]. However, accurate pressure-dependent data are rare and not available

commercially. The actual testing is time consuming, expensive, and test equipment is

not commonly available [Ainoya and Amono, 2001]. The heat transfer coefficient

between the part and mold wall changes with time and operating variables. It affects the

cooling time and melt pressure. However, it is usually a constant in commercial CAE

packages. For example, both C-MOLD and MoldFlow set a default value of 25,000

W/m2⋅K, which result in higher predicted cavity pressure. Chen, et al. [2000] noticed

that material properties might be the reason for the prediction discrepancy. Ainoya and

Amono [2001] found that pvT-data affected fill time and cavity pressure. They also

found that the heat transfer coefficient and pressure-dependent viscosity had a great

effect on pressure prediction. Cavity pressure drop was extremely overpredicted when

the effect of pressure on viscosity and juncture loss were not considered. Slightly lower

filling pressure was predicted when the tabulated heat capacity was used instead of

36

constant heat capacity. However, the thermal conductivity had little influence on filling

pressure. Sherbelis and Friedl found that neglecting the effect of pressure on viscosity

led to overprediction of cavity pressure, while neglecting the juncture loss led to

underprediction of nozzle pressure [Sherbelis and Friedl, 1996]. Sridhar and Narh

[1999] found that the heat capacity and thermal conductivity had almost no effect on

cavity pressure, but they could affect cooling time and part shrinkage and warpage.

Another cause for the discrepancy between simulation and experiment is the lack of a

high quality database for the polymer, such as heat conductivity and pvT data [Chen, et

al., 2000]. For example, viscosity and thermal properties are usually measured under

equilibrium conditions, and they greatly affect simulation accuracy when these

properties, such as pvT data, are used in non-equilibrium injection molding process

[Chen, et al., 2000]. Furthermore, the difference may result from the difference between

the actual molding conditions and set conditions. For example, the actual melt

temperature and injection velocity may be greatly different from the set parameters

[Ainoya and Amono, 2001]. Thus the set parameters do not reflect the actual melt

conditions and using these parameters for simulation results in the difference between

the simulation results and experimental results.

Some work has been conducted to study the effect of material properties on

pressure. However, a systematic study of the effect of these parameters is rare. In this

study, the effect of pressure-dependent viscosity, heat capacity, heat transfer coefficient,

juncture pressure loss and pvT-data on cavity pressure and pressure drop prediction will

be considered, and the importance of each parameter will be evaluated. Then the

37

simulation results and measured data will be compared. Finally the method to improve

the prediction accuracy will also be discussed. The study aims to help in understanding

which material property is important and needs rigorous testing, in order to improve

simulation accuracy and reduce time and cost for expensive property testing.

2.3 REUSE of HIPS

As the demand for plastics is increasing, the disposal of plastics is also

increasing. World thermoplastic consumption was over 100 million kilograms in 2000

[Society of the Plastics Industry, 2001]. However, only approximately 5.4% of post-

consumer plastics was recovered in the US [U.S. Environmental Protection Agency,

2002]. Plastics recycling is important because more efficient re-use of materials will

reduce the quantities of plastics sent to landfills as well as reduce raw material

extraction. Waste prevention practices are increasingly significant and are increasingly

encouraged with the advent of “take-back” legislation [Gamalski, 1996; Meffert and

Kirchgeorg, 1997; Hubschman, et al., 1995]. It is accepted that direct use of post-

consumer polymer is the most efficient and reliable way to treat plastic waste [Kartalis,

et al., 1999]. However, how to characterize the post-consumer resin and how to increase

the percentage of the post-consumer resin are two of the problems in recycling plastic.

High impact polystyrene (HIPS) occupies a large market share in computer,

business machines, and other electronics [Arola and Legarth, 1999]. Furthermore,

monitor housings and printers are two of the largest applications. However, less than

38

1% is recovered from the total 19% market share of HIPS [Dillon and Aqua, 2000].

Therefore, it is important to evaluate and develop viable options for discarded polymer

products. However, the analysis of life cycle trade-offs between use of recycled plastics,

recyclability, reduction of process wastes, energy consumption, yields, and product

performance are complex [Allenby and Laudise, 1995; Stuart, et al., 1999; Szekely and

Laudise, 1995]. To date, many companies process either 100% virgin material or virgin

material with small percentages of regrind. Sources of post-industrial regrind may be

internal or from another industrial processor(s). Companies embracing product

stewardship are struggling to develop viable approaches to process and recycle returned

products economically. Post-consumer polymers may be contaminated by other

materials [Langerak, 1997]; post-consumer products may contain polymer blends as well

as additives such as reinforcements, paint, or flame retardants [Dillon, 1999]. Thus,

post-consumer plastics introduce additional raw material uncertainties into the

manufacturing process. In addition, incompatible polymer blends may be present in a

product, requiring expensive disassembly procedures or less valuable mixtures. As a

result, many plastics recyclers currently select between options such as incineration or

downcycling, the formation of lower grade polymer materials. Another complication is

that returned polymers have been exposed to various thermal and mechanical conditions

and degradation could happen.

One important challenge in post consumer resin recycling is the contamination

from other materials. If the contaminants are not removed, then the mixed materials may

be “down-cycled” for use in simpler applications than their original products.

39

Contaminants may be metal, stickers, or other polymers. The level of contamination in

post-consumer resins depends on the product design and the separation techniques used.

After hazardous materials such as batteries are removed manually, disassembly or

automatic size reduction (shredding) follows. Separation techniques may include

manual labor, magnets, air separation, or float sink approaches [Hendrix, et al., 1996].

Langerak [1997] compared there different separation methods for television housings:

(1) complete manual disassembly; (2) manual removal of front and back casings,

shredding, magnetic ferrous metal removal, and float-sink separation of nonferrous

metals and plastics; and (3) complete shredding, magnetic ferrous metal removal, and

float-sink separation of nonferrous metals and plastics. Langerak concluded that option

2 was the most cost effective materials recovery method. Because many variations of

plastics have similar densities, plastics identification based on density may not be

sufficient. So, contamination is still a concern because option 2 relies on density

separation.

Furthermore, identification marks usually appear at the most general level, such

as low-density polyethylene, and do not include information such as the manufacturer

product code or manufacturer. Even recyclers with close relationships with

manufacturers and suppliers and sophisticated information links have faced challenges to

identify materials from the model number [Grenchus, et al., 1998]. Moreover, the

source of plastics collected is correlated to the age and diversity of the materials. For

example, the plastics from municipal solid waste collection will be older and contains

40

more diverse assortment than the plastics from post-industrial regrind. Thus, further

characterization of the actual post-consumer resins is required through testing.

Another big challenge is the material degradation. During polymer processing,

such as injection molding, materials undergo severe thermal histories and mechanical

loadings (shear and extensional flows) that produce molecular degradation. Molecular

degradation of plastics usually decreases the polymer chain length and leads to a

decrease in melt viscosity and mechanical properties of the final product. The degree of

degradation varies significantly depending on the type and amount of polymer and

additives used in each commercial resin. Blending polymers for recycling has been

studied in the context of improving the properties of PCR [Liu and Bertilsson, 1999].

Several researchers have studied property degradation during thermoplastic

recycling processes. Ries and Menges [1988] studied the degradation of polypropylene

and found a decrease in impact strength due to a decrease in molecular weight. They

believed that the melt index could be useful in predicting the molecular weight, which

may allow off-line monitoring of impact strength degradation. Zahavich, et al. [1992]

showed that viscosity and swell ratio are the best indicators for degradation of an HDPE

resin. This is not surprising, since swell ratio is a strong function of the high molecular

weight fraction. Pagel [1989] showed that reground ABS exhibits very stable physical

properties over successive regrind generations, but the resins became yellow.

Dzeskiewicz, et al. [1993] studied the decrease in mechanical and rheological properties

of glass-filled nylon with successive generations, but showed that more than 50%

regrind could be blended with virgin resin to exceed specifications.

41

The degradation of polymer chains due to mechanical stresses (shear and

extensional flows) has been an object of scientific interest for at least 50 years, starting

with the Frenkel’s work [Frenkel, 1944]. Using a bead-spring model, Frenkel predicted

that the polymer chains would align with the flow, that the stress would be maximum in

the middle of the chain, and that as a result the middle of the chain would be the site of

fracture. Scientists have observed mid chain fracture for a variety of polymers under

various flow conditions. The flow birefringence experiment on polystyrene showed that

the degradation products formed a narrow distribution around half the molecular weight

of the initial polymer molecules [Odell and Keller, 1986]. Nguyen and Kausch [1986]

studied the degradation of polystyrene in a different flow device, and found that the

polymer degraded to a broad molecular weight distribution. These studies point to the

importance of understanding how thermal history and mechanical stresses impact

polymer degradation.

Studies have been conducted on determining the number of cycles a polymer can

be molded [Shriver, et al., 1994; Bernardo, et al., 1996]. Bernardo, et al. [1996]

developed a model to predict the properties of virgin/recycled polymer mixes based on

the number of previous processing cycles. This information is useful in determining the

materials recycling threshold for polymer components. In isolated cases where housings

are returned to the original manufacturer, the number of cycles may be tracked

[Timmons, 1998]. However, in most cases, it is not viable to track the number of

processing cycles.

42

To use PCR, it is important to decide the processing parameters quickly in

injection molding application. However, the challenge is how to characterize the PCR in

order to injection mold it. Suppliers of virgin materials provide ranges of typical

property values for tensile strength, tensile modulus, impact, mold shrinkage, and other

characteristics [GE Plastics, 1992]. Some companies seek used polymers with

certification of their mechanical properties [Jones, 1996]. Furthermore, manufacturers

often use mold filling simulation software with virgin resin databases to reduce the time

to determine initial processing parameters. A major gap is that current databases do not

contain entries for used resins. Although Narh, et al. [1999] investigated the viscosity

and injection molding processing parameters for post-consumer ABS, PC, and nylon 5.5,

with mold-filling simulation and design software, they did not specify how they obtain

their inputs for the PCR in a mold-filling simulation. Without material characteristic

data of the PCR, molders cannot easily determine whether a PCR may be a candidate for

use alone or in blends with virgin resins depending on the material characteristics and

the complexity of the application. Designers are hesitant to include post-consumer

recycled material content. Further complicating the inclusion of recycled materials is the

uncertainty of material content, contaminants, and degradation [Eriksson, et al., 1998].

In this study, we describe our progress in evaluating the viability of reusing post-

consumer and virgin polymer blends of high impact polystyrene from electronics

equipment housings. The study also introduces a new approach to determine initial

processing parameters for injection molding of post-consumer resin.

43

a. Alternate dull and glossy regions.

b. Synchronous dull and glossy regions.

Fig. 2.1. Alternate and synchronous dull and glossy flow marks.

λ

Dull regions are out of phase onthe top and the bottom

Dull region

λ

Dull regions are on the phaseon the top and the bottom

Dull region

44

Fig. 2.2. Thin-Wall plat with microstructures.

Main flow direction

Microchannels

45

CHAPTER 3

FLOW MARKS DURING THIN-WALL INJECTION MOLDING

3.1 ALTERNATE DULL AND GLOSSY FLOW MARKS

3.1.1 Introduction

Several kinds of surface defects may occur during injection molding. One type

of surface defect is characterized as alternate dull and glossy surfaces in which flow

marks on one side of the part are out of phase with those on the other side [Yokoi,

1994a], as shown in Fig. 3.1. This is often referred to as tiger striping. This surface

defect occurs especially on automotive exterior parts. Some work has been done to

explain and eliminate flow marks [Yokoi, 1994b; Chang, 1996a; Chang, 1996b; Hobbs,

1996; Heuzey, et al., 1997; Hamada and Tsunasawa, 1996; Dharia, 1999; Bulters and

Schepens, 2000; Grillet, et al., 2000; Charmeau, et al., 2000; Xu and Koelling, 2001;

Jayaraman, 2002]. Several mechanisms have been proposed to explain the generation of

flow marks. However, little has been truly understood on why flow marks occur and

how to predict and eliminate them. A slip mechanism was proposed by Chang [Chang,

1996a; Chang, 1996b]: When the melt has low adhesion to the mold surface, slip can

occur and initiate a melt flow instability. Thus, this kind of flow instability can cause

46

flow marks with alternate dull and glossy regions. Hobbs believed that stick/slip flow at

high wall shear stresses caused flow marks [Hobbs, 1996]. Conversely, Heuzey, et al.

[1997] found that there was no obvious relationship between the wall slip and flow

marks. Furthermore, coating on a mold wall did not affect the occurrence of flow marks.

They believed that the generation of flow marks was due to the filamentation and

stretching of semi-solidified materials. Hamada and Tsunasawa [1996] found that in

cases where flow marks occurred, the PC and ABS flow oscillated, while in cases where

no flow marks occurred, the PC and ABS flowed in steady laminar motion with a normal

fountain flow. In a study of binary blends of polypropylene and ethylene co or ter-

polymers, Dharia [1999] proposed that the flow marks were generated by melt flow

instability and the inability of melt to recover from the stress changes at the flow front.

More recently, Bulters and Schepens claimed that flow marks resulted from a flow front

instability [Bulters and Schepens, 2000]. Furthermore, Grillet, et al. conducted a linear

stability analysis and found that the most unstable eigenvector was an oscillatory,

swirling flow near the stagnation point at the free surface [Grillet, et al., 2000].

The effect of operating variables, physical properties of plastics, and mold

geometry has been discussed. Although experimental evidences show that oscillating

instabilities occurred in mold filling [Chang, 1996a; Hamada and Tsunasawa, 1996;

Bulters and Schepens, 2000], there is disagreement on why the instability occurs and

where it originates. In this section, we study the effect of operating parameters and

different polymer melts on the wavelength, width, and gloss variation of the flow marks.

Then several methods to reduce the flow marks are discussed. Furthermore, it is widely

47

known that elastic instability occurs upstream of a contraction, such as a capillary die or

slit die, in extrusion or spinning [Piau, et al., 1988; White, et al., 1987; Boger and

Walters, 1993; Koelling and Prud’homme, 1991]. However, the researchers studying the

flow marks have not studied the entry instability and its relationship to the flow marks,

although Dharia already noticed the similarity between extrusion and injection molding

processes [Dharia, 1999]. We study the correlation between gross melt fracture in

extrusion and alternate dull and glossy flow marks in injection molding, then propose an

entry viscoelastic flow instability mechanism to explain the alternate flow marks.

3.1.2 Experimental

Molding experiments were conducted on a Sumitomo SG M-HP 180-ton

injection molding machine. The materials used were four types of polypropylenes,

namely PP-A, PP-B, PP-C and PP-D. Two spiral molds were employed with different

thicknesses (1.58 and 3.17 mm). The width of the mold channel was 1". The total flow

length was 16". The melt temperature was 204.4, 223.9 and 232.2°C. The mold

temperature for most experiments was set at a constant value of 29.4°C. The mold

temperature was changed to 79.4, 51.7, and later to 18.3°C. Two rectangular molds

were also employed with a thickness of 5.08 and 1mm. The length and width of the

mold channels was 150 and 51 mm, respectively. The edge gates used were 2.54 and 0.5

mm in thickness for the thick and thin mold, respectively. The melt temperature was

190, 225 and 260°C. The mold temperature ranged from 22 to 85°C. The effect of

48

holding pressure and injection pressure was studied at melt temperature 190°C, mold

temperature 22°C, and injection speed 0.4 m/s where the flow marks were pronounced.

For the parts that exhibited tiger striping marks, the wavelength λ was measured.

The wavelength λ was the distance from one shiny region to another on one side. We

also measured stripe width, which was the width of one shiny region.

The rheological properties were measured by a Rheometrics RMS 800. The

complex viscosity, storage and loss modulus, and first normal stress difference of each

polypropylene sample were measured at 180, 200, and 220°C, respectively. The

extensional viscosity was measured at 130°C by a tensile tester, Instron 8511, based on

the standard ASTM test. The samples were standard tensile bars with 13 mm in narrow-

section width, 57 mm in total length, and 3.2 mm in thickness. To obtain a constant

strain rate, one needs to program the Instron machine to follow the exponential-type

increase of sample length. The viscosity-molecular weight was measured based on

ASTM D445-97.

To check the slip effect, Dynamar 9613 (a 3M product), a fluorocarbon

elastomer, was used as a coating agent. It is a slip promoting product. Its dilute acetone

solution, ca. 1%, was coated on the hot mold surfaces to allow evaporation of the

solvent. We also studied the disappearance of the flow marks by directly adding a small

amount of Dynamar, 0.2%, into the PP-C pellets. The resin was well mixed before tests.

Samples were collected after 100 shots to stablize.

A Differential Scanning Calorimeter (DSC) from TA Instruments, DSC 2920,

was used to measure the crystallinity of dull and shiny regions. The sample was scanned

49

from 30 to 200°C at the rate of 10°C/min. A Scanning Electron Microscope (SEM),

Philips XL 30, was employed to observe the morphology of dull and shiny regions. An

optical profilometer, Wyko NT330, was used to measure the roughness of the dull and

shiny regions.

A two-stage single-screw extruder (Rheomex 252p) from Haake was applied to

exam the melt fracture phenomenon that usually shows up with PP. The screw had a

diameter of 3/4 inch and a length to diameter ratio (L/D) of 25. The diameter of the

capillary die used was 1.2 mm and its length was 12.

Because it is very difficult to estimate the wall shear stress during mold filling,

C-MOLD 2000 was used to simulate filling our spiral molds. C-MOLD is a set of

integrated computer aided engineering (CAE) simulations for plastics molding

processes, including injection mold filling, post-filling and cooling, part shrinkage and

warpage. CAE provides an easy-to-use data visualizer for viewing mesh information

and analysis results. First, the geometry was built, and then a mesh with 672 elements

was set up for C-MOLD simulation. In the simulation, all four types of polypropylenes

were adopted in both thin and thick molds. Moldflow Plastics Insight (MPI) 3.0, a

software integrating C-MOLD 2000 and Moldflow Plastics Insight 2.0, was used to

simulate filling our rectangular molds to estimate the wall shear stress at the gate. The

geometry and the mesh with 754 elements built in C-MOLD was imported and then the

simulation was run on MPI 3.0. In the simulation, the values of the processing

parameters, such as shot size, injection pressure, holding pressure, holding time, mold

50

temperature and cooling time, were the same as those in the real injection molding

processes.

3.1.3 Results and Discussion

3.1.3.1 Rheological Characterization

The complex viscosity of PP-A, PP-B, PP-C, and PP-D was measured at 180,

200 and 220oC, respectively. Fig. 3.2 shows the complex viscosity of four polymer

melts at 200oC. It was found that the complex viscosity decreased with an increase in

frequency, and PP-C had the largest viscosity at the same frequency. Fig. 3.3 shows the

complex viscosity of PP-C at different temperatures. Fig. 3.4 shows the storage modulus

and loss modulus of different PPs at 200oC. It was found that the storage modulus and

loss modulus of PP-C were the largest. Also we can see that the storage modulus of PP-

C was very close to its loss modulus, as compared to other PPs. Fig. 3.5 shows the first

normal stress difference N1 versus shear rate at 200oC. PP-C had the largest N1 at the

same shear rate. Fig. 3.6 shows the first normal stress difference N1 versus shear rate at

180, 200 and 220oC, respectively. Fig. 3.7 shows the transient extensional viscosity at

130oC when the strain rate was 0.01 s-1. It was found that PP-C had the largest

extensional viscosity at the same moment. It was also found that in the range of tested

shear rate and time, the ratio of N1/extensional stress was PP-C > PP-D > PP-A or PP-B

at the same conditions.

To determine relaxation time, we shifted all dynamic viscosity η' and elastic

material function 2η"/ω data to the master curve at 200oC using time-temperature

51

superposition and fit the data with the 1-mode Giesekus model [Bird, et al., 1987], as

follows:

An example is shown in Fig. 4.8. The relaxation time determined from the

model fit for different materials is shown in Table 3.1. We found that PP-C had the

longest relaxation time, and therefore the largest Deborah number (De=λ•γ ) at the same

shear rate. Thus PP-C is the easiest material to develop a viscoelastic flow instability.

The viscosity-molecular weight of all four polymers measured is listed in Table 3.2.

3.1.3.2 Injection Molding Results

Experimental trials were conducted in the spiral molds at first. It was found that

PP-A and PP-D did not generate flow marks. However, flow marks usually occurred for

PP-C and PP-B under a certain range of processing conditions. The flow marks are

generally out of phase between the top and the bottom of the part. However, the shiny

region on one surface is not exactly in the center of two neighboring shiny regions on the

opposite surface. The flow marks that occurred were characterized as alternate dull and

shiny regions. Flow marks of PP-C occurred when the flow front velocity was as low as

0.01 m/s for the thick mold and 0.1 m/s for the thin mold. When the injection speed was

.

SS γητ −=

.

PPPP

1P11P γη}.τ{τ

η

λατλτ −=−+

PS τττ +=

52

very low, the flow marks occurred at the end of the flow length. They did not occur

immediately after the distance of about one wavelength from the gate. With the increase

of the injection speed, flow marks became more pronounced. When the injection speed

was higher, flow marks occurred immediately after the polymer melt entered the mold

cavity. Also, the flow marks were very pronounced. When the injection speed was

increased further, flow marks became dimmer. When the injection speed was above a

critical value the flow marks disappeared. The width and discernible level of shiny

regions changed along the flow length. Usually, flow marks at the end of the flow length

were pronounced. Even for the same shiny region, the width changed in the width

direction. Usually, the shape of the shiny region also changed along the flow length, and

in some cases irregular shapes appeared. Fig. 3.9 shows a typical set of samples of flow

marks for PP-C.

For PP-B, the flow marks are similar to those of PP-C. However, because of the

filler, the color of the molded parts was yellowish and the flow marks were less

pronounced, making it very difficult to distinguish the neighboring dull and shiny

regions. Although we can notice the flow marks, it is very difficult to measure the

wavelength and width of the flow marks except in a narrow range of flow front velocity

at which the flow marks are apparent. It was observed that the wavelength and width

increased with the increase of flow front velocity. Above a critical flow front velocity,

the flow marks disappeared. Although the wavelength is close to the wavelength of PP-

C at the same conditions, the width of flow marks of PP-B is narrower compared to that

of PP-C.

53

In the thick rectangular mold, the alternate dull and shiny flow marks of PP-C

only occurred above a certain injection speed. At first the flow marks gradually became

more pronounced as the injection speed was increased; however, with the further

increase of injection speeds, the flow marks became less visible and finally disappeared.

This phenomenon is somewhat different from other researchers’ observations that the

flow marks became more severe as the injection speed increased [Chang, 1996b; Hobbs,

1996; Heuzey, et al., 1997]. A typical example of alternate dull and glossy flow marks is

shown in Fig. 3.10. In the thin rectangular mold, alternate dull and shiny flow marks of

PP-C occurred once the mold was filled.

The wavelength and stripe width of the flow marks of PP-C were measured. The

wavelength is defined as the distance from one shiny region to another on one side,

while the stripe width is the width of a single shiny region. Fig. 3.11 shows the effect of

flow front velocity on the wavelength in the thin mold. It was found that for the thin

mold the wavelength increased with an increase in flow front velocity, and then

remained relatively constant. Moreover, the wavelength was almost the same at the

same flow front velocity. However, the higher the melt temperature, the longer the final

wavelength. Fig. 3.12 shows that the mold temperature has little effect at low flow front

velocities; however, at higher flow front velocities, the higher the mold temperature, the

longer the wavelength. Fig. 3.13 shows that the thicker mold exhibits a longer

wavelength. Thus a longer wavelength can be contributed to a higher melt temperature,

a higher mold temperature, and a thick mold. Fig. 3.14 shows the effect of melt

temperature on the width of the shiny stripes in the thin mold. It was found that the

54

width of the shiny stripes increased with an increase in the flow front velocity. At a low

flow front velocity, the melt temperature had little effect on the width of the shiny

stripes; however, at a higher flow front velocity, the higher the melt temperature, the

wider the shiny stripes. Fig. 3.15 shows that the mold temperature does not have much

effect when the flow front velocity is small, yet the width of the shiny stripes increases

as the mold temperature is increased at a high flow front velocity. The trend of the

change of the width is very similar to the trend of the change of the wavelength. Fig.

3.16 illustrates that the width of the shiny stripes increases with the increase of mold

thickness. Compared to previous work [Xu and Koelling, 2001], the effect of mold

temperature and melt temperature was clearly observed in the rectangular molds.

For the gloss variation of the flow marks of PP-C in the thin rectangular mold, it

was found that increasing either melt or mold temperature made the flow marks less

visible. The observed effect of mold temperature and thickness is in agreement with

Chang’s work [Chang, 1996a; Chang, 1996b]. The effect of melt temperature in our

experiment agrees with Hamada and Tsunasawa’s result [Hamada and Tsunasawa,

1996]. It was found for the first time that the flow marks were less visible as the holding

pressure was increased. However, injection pressure had almost no effect on the

visibility of the flow marks, which was different from other researchers’ observations

[Chang, 1996b; Dharia, 1999].

Furthermore, the effect of the molecular weight of PP-C was studied. Adding

20% PP-D into PP-C greatly alleviated the flow marks, and the flow marks were scarcely

55

visible compared to pure PP-C at the same operating conditions. However, adding 20%

PP-A had little effect.

From the above discussion, the flow marks could be reduced by one or more of

the following factors: high injection speed, high melt or mold temperature, mold surface

coatings, and/or changing molecular weight or its distribution.

The flow marks occurred only above a certain flow front velocity in the thick

mold, Vcri. It was further found that the mold temperature almost had no effect on Vcri.

Vcri scarcely changed at different mold temperatures. However, Vcri increased as the

melt temperature was increased, as shown in Fig. 3.17.

The effect of the coating on the surfaces of the mold or gate was also studied. It

was found that a coating on the mold surfaces could not prevent the occurrence of the

flow marks, although it could alleviate the flow marks and make them less pronounced.

One interesting phenomenon is that coating on the mold surfaces did not change the Vcri,

implying that slip is not the cause of the alternate flow marks. The reason is that coating

on the mold surface reduces the critical shear stress where the slip occurs, thus

decreasing the Vcri where the slip is triggered.

Another interesting phenomenon observed was that the flow marks disappeared

at high injection speeds, which has not been reported previously. We define it as the

transition velocity, above which the flow marks disappear. Fig. 3.18 shows the

transition flow front velocity vs. melt temperature. It was found that the transition

velocity increased as the melt temperature was increased. However, the mold

56

temperature almost had no effect on the Vtrans. The zone of the flow marks in which the

flow marks may occur in operation is shown in Fig. 3.19.

It was found through our experiment that mold surface coatings increased the

Vtran. It was further found that adding 0.2% Dynamar into PP-C also increased the Vtrans.

It is well known that a slippery surface or adding a small amount of fluorelastomer into

the polymer reduces the wall shear stress at which slip occurs [Yang, et al., 1998;

Kazatchkov, et al., 1995]. This implies that the slip is not the cause for the

disappearance of the flow marks at high injection speeds. The reason is that the slippery

surface or the addition of Dynamar decreases the wall shear stress where slip occurs,

thus decreasing the Vtrans at the same operating variables. Therefore, slip does not cause

the flow marks to disappear. Their disappearance may be due to the higher melt

temperature induced by high flow front velocity, and thus greater shear heating.

3.1.3.3 Morphology and Crystallinity

The Differential Scanning Calorimeter (DSC) experiment showed that no

difference in crystallinity was observed between the dull and shiny regions. The sample

thickness was about 100 micrometers. From the scanning electron micrograph (SEM), it

was found that polymer molecules were highly oriented in the shiny region, but the

polymer molecules were only slightly oriented in the dull region, as shown in Fig. 3.20.

This is in agreement with other researchers’ results, except that either high orientation or

no orientation was observed for shiny regions [Charmeau, et al., 2000]. The measured

average roughness by optical profilometer was smaller in shiny regions than in dull

57

regions, as shown in Table 3.3. The reported average roughness is the average value of 5

randomly selected positions.

3.1.3.4 Extrusion

The PP was extruded at the die temperature 170°C. It was found that when the

wall shear stress was low the extrudate was smooth, but gross melt fracture occurred at

higher wall shear stresses. The extrudate irregularity was wavy, as shown in Fig. 3.21.

The wall shear stress was estimated by DL

P

/4

∆ without the Bagley correction, where ∆P

is the pressure drop in the die, L is the die length, and D is the diameter of the die. The

apparent shear rate was calculated by 3

32

D

Q

π, where Q is volumetric flow rate [Macosko,

1994]. The experiment showed that the critical wall shear stress for the onset of the

gross melt fracture was 0.13 MPa. This is in agreement with other researchers' results

[Kazatchkov, et al., 1995]. The flow curve is shown in Fig. 3.22.

3.1.3.5 Simulation

It is very difficult to obtain wall shear stress and temperature profiles during

filling the spiral molds. By the C-MOLD simulation, the wall shear stress at the center

of flow front was obtained. Fig. 3.23 shows the wall shear stress of different polymer

melts vs. filling percentage at the injection speed of 0.1 inch/s in the thick mold. It was

found that generally, the wall shear stress of PP-C > PP-D > PP-B > PP-A at the same

58

filling percentage. At the same operating conditions with an injection speed of 0.1

inch/s, melt temperature of 204.4°C, and mold temperature of 29.4°C, the wall shear

stress of PP-C was about 0.13 MPa, while PP-B was only about 0.05 MPa. 0.05 MPa is

much smaller than 0.13 MPa above which macroscopic slip usually occurs for PP

[Kazatchkov, et al., 1995; Hatzikiriakos, 1991]. However, our experiment showed that

PP-B usually had flow marks. PP-D showed no flow marks, although its wall shear

stress was larger than that of PP-B. It was concluded that slip is unlikely the reason for

the generation of the flow marks in our case. Furthermore, slip could not explain why

the flow marks disappear at even higher injection speeds.

MPI 3.0 was used to obtain the wall shear stress during filling of the rectangular

mold. The critical wall shear stresses of PP-C at the middle of the gate were obtained at

Vcri where the flow marks began to form. The processing parameters and the Vcri used

had been determined from the injection molding experiment. Fig. 3.24 shows the critical

wall shear stress at the middle of the gate at different melt temperatures. It was found

that the wall shear stresses were in a narrow range. That means the flow marks start to

form at a wall shear stress of around 0.24 MPa at the gate at different melt temperatures.

Fig. 3.25 shows the critical wall shear stress at the middle of the gate vs. the filling

percentage at different mold temperatures. The figure shows that the wall shear stress

generally was very close at different mold temperatures. From the simulation, it was

found that flow marks of PP-C started at the same critical wall shear stress almost

independent of melt or mold temperature.

59

3.1.3.6 Mechanism

In injection molding, the process that polymer melts experience is similar to that

in extrusion. The general picture of these processes is that the polymer melt meets a

contraction and experiences high shear at the die or gate, then the polymer melt leaves

the die or gate and the polymer molecular chains relax, as shown in the following Fig.

3.26. Therefore, the melt fracture in extrusion processes and the flow marks in injection

molding are related, although a difference in the movement of polymer melts exists

between extrusion and injection. In extrusion processes, the shear rate at the die is on

the order of 1000 1/s [Schramm, 1994]. After the melt leaves the die, the melt swells

and moves like a plug flow with a free boundary. The shear rate is zero and the shear

stress at the surface is zero if we neglect the small extension near the surface. For

injection molding processes, the shear rate in the gate is higher than in the die. After the

melt leaves the gate, the melt moves in the mold, but the swell of the melt is restricted by

the mold wall because of the rigid boundary. Also the wall shear rate and wall shear

stress are still large, although they are much smaller than in the gate. The shear rate is

on the order of 10,000 1/s in the nozzle.

In extrusion processes, when the shear stress is low, the surface of extrudates is

smooth. However, flow instabilities occur when the stresses are sufficiently high. The

extrusion stability is associated with the appearance of distortion on the extrudate

surface, sometimes accompanied by oscillatory flow. Usually, melt fracture is a general

term used to describe different irregularities and instabilities that generate distortions and

non-smooth surfaces. Denn proposed a set of instabilities of LLDPE [Denn, 1990;

60

Denn, 2001]. When the shear stress reaches a critical value, typically about 0.1 MPa, the

surface becomes rough and wavy, which is commonly called sharkskin or surface melt

fracture. This type of irregularity with wavelengths is much smaller than the capillary

radius, and is about 1/10-1/5 of the overall specimen diameter [Loenov and Prokunin,

1994]. At a higher stress, the alternate smooth and sharkskin occurs. It is known as slip-

stick, or spurt flow. At a still higher stress, a transition region occurs where the surface

is relatively smooth with long-wavelength distortion. At a much higher stress, gross or

wavy distortion occurs. The wavelength is about the specimen diameter [Loenov and

Prokunin, 1994]. This set of phenomena is common for linear polymer melt, such as

HDPE, LLDPE, and PBD. However, most branched polymers do not show sharkskin or

slip-stick regions [Denn, 2001]. They only exhibit gross distortion. Sometimes

extrudates exhibit smooth surfaces again when the stress is much higher than the stress

where gross melt fracture occurs. It is commonly known as superextrusion and was well

reviewed by Leonov, et al. [Loenov and Prokunin, 1994]. It is believed to result from

the uniform slip along the die.

The gross melt fracture has been studied for more than 50 years. However,

controversy still exists about the melt fracture phenomenon [Piau and Agassant, 1996;

Piau, et al., 1990a]. There are two common mechanisms in the literature to explain the

melt fracture [Piau and Agassant, 1996]. Some researchers believe that slip at the die

wall is the origin of the melt fracture. However, Den Otter clearly showed that wall slip

at the die could not explain the melt fracture [Den Otter, 1970]. Most researchers agree

that an entry instability causes gross melt fracture [Piau and Agassant, 1996; Larson,

61

1992]. The instability is also affected by various properties, such as polymer structure,

geometry of die entry, melt temperature, and die temperature [Piau and Agassant, 1996].

For viscoelastic fluids, a Newtonian fluid-like corner vortex may occur at a low

flow rate. The streamlines are the same as those of Newtonian creeping flow with a

small corner vortex, named "Moffatt eddy". The corner vortex zone is a dead zone that

does not interact with the fluid outside. The formation of vortices may be due to the

increasing extensional viscosity with the deformation rate or also due to the shear-

thinning effect [Den Otter, 1970; Cogswell, 1972]. Two different pathways are possible

for the development and growth of vortices as the flow rate is increased [Rothstein and

McKinley, 1999; Rothstein and McKinley, 2001]. For some viscoelastic fluids, the

corner vortex grows in strength as the flow rate is increased [Yesilata, et al., 1990]. At a

very high flow rate, the corner vortex grows upstream, fluctuates, and makes the flow

field entirely unstable. For some other viscoelastic fluids, two types of vortices coexist.

One is the corner vortex, and the other is the lip vortex [Yesilata, et al., 1999]. As the

flow rate is increased, corner vortex and lip vortex recirculating areas expand; then lip

vortex gradually develops and invades the corner vortex, and finally generates a single

area of recirculation [Piau and Agassant, 1996]. At a still higher flow rate, the flow

becomes unstable, and the vortex pulsates or rotates, causing a global change of flow

structure [Rothstein and McKinley, 2001; Boger, et al., 1986]. It is yet not clear whether

lip vortices occur for a given viscoelastic fluid. However, researchers found that its

occurrence depends on fluids and contraction ratio, i.e. the ratio of diameter upstream to

the diameter of the contraction [White, et al., 1987; Rothstein and McKinley, 1999].

62

It was found that the development of upstream instabilities governed the

appearance of the extrudates and the helix pitch. Above a critical stress, the flow

instability occurs independent of downstream flow conditions [Piau, et al., 1990b]. The

melt fracture occurs when the vortex is unstable. The amplitude and frequency of

pulsation increases with the pressure [Piau and Agassant, 1996]. Usually the frequency

of surface distortion and the vortex pulsation is identical.

As a result, we expect that vortices may form and an instability may happen at

the entry in injection molding when the flow rate is high enough, since extrusion

processes and injection molding processes are similar although differences exist between

extrusion and injection molding. The oscillating entry instability can propagate and

affect the downstream flow. Thus, the symmetrical oscillating flow may occur in the

mold, and the different thermal and shearing history of the melt causes alternate flow

marks. In fact, the oscillating flow has been found in other researchers’ experiments

[Hamada and Tsunasawa, 1996; Bulters and Schepens, 2000; Yokoi, 1994b]. Our

experiment showed that PP-C exhibited gross melt fracture at a high flow rate, i.e., the

entry instability occurred before a contraction, although the surface is smooth at a low

flow rate. It is therefore not surprising that the PP-C exhibits alternate dull and glossy

flow marks. As discussed above, slip is not the reason for the generation of the flow

marks. Some researchers [Xu and Koelling, 2002; Heuzey, 1997] already excluded slip

as the possible reason. It is also well known that PP behaves like a branched polymer.

This means that its molecular chains are not highly entangled and so the slip-stick

phenomenon does not occur.

63

One interesting question is why so many polymers exhibit gross melt fracture, yet

fewer polymers are reported as apparently showing flow marks. The reason may be due

to the different geometry of contraction used in extrusion and injection mold processes.

It was found that the symmetrical contraction generates vortex more easily than a non-

symmetrical contraction, such as planar die [White, et al, 1987]. Many researchers used

capillary die in extrusion, while most gates in injection are usually not symmetrical.

Viscoelastic melts therefore show vortices and thus gross melt fracture in extrusion, but

are less likely to exhibit vortices in injection molding (and thus flow marks).

This mechanism could explain our experimental results of flow marks. At a low

injection speed, the flow is stable and no flow marks occur. At a high injection speed

that reaches a critical wall shear stress, an entry flow instability occurs, resulting in

symmetrical oscillating flow that generates alternate flow marks, as shown in Fig. 3.27.

As the injection speed increases, the wall shear stress increases. The melt becomes more

severely sheared and the flow marks become more pronounced. However, with a further

increase of the injection speed, shear heating becomes more important and the melt

temperature is increased. This may make molecular chains easier to relax and thus less

sheared, so the flow marks are less visible. Finally, the flow marks disappear.

Increasing the melt temperature or mold temperature decreases the wall shear stress and

thus makes the flow marks less visible. The effect of holding pressure is complicated. It

may be explained as follows: Although increasing the holding pressure increases the

wall shear stress, the high viscous heating increases melt temperature and thus makes the

flow marks less visible. The effect of injection pressure was very unusual, although it

was probably overshadowed by the effect of holding pressure in our case. So no clear

64

effect of injection pressure on the visibility of the flow marks was observed in our

experiment. People found that the frequency and amplitude of the vortex increased with

the increase of flow rate [Den Otter, 1970]. So the wavelength and width of the flow

marks increased as the flow front velocity was increased. Furthermore, the frequency

increased with the increase of flow front velocity, as shown in Fig. 3.28. The trend of

frequency is similar to that of gross melt fracture in extrusion [Den Otter, 1970].

Increasing the melt or mold temperature may increase both the wavelength and the width

of the flow marks. This may be explained as follows: The increase of melt or mold

temperature decreases wall shear stress, causing a more stable entry flow. The

molecules relax and move more easily in the mold cavity. As for the effect of the mold

thickness, the oscillating flow has more space to move before it hits the mold wall and

bounces back in the thick mold although the gate wall shear stress is smaller. So the

wavelength and width would be larger. It is well known that the gross melt fracture

(entry instability) happens at a critical wall shear stress, independent of temperature

[Kazatchkov, et al., 1995]. So, as the melt temperature is increased, flow marks occur at

higher flow front flow velocities to reach the same critical wall shear stress, i.e., Vcri

increases with the increase of the melt temperature. However, mold temperature had

little effect on the wall shear stress in our case, so the flow marks happened almost at the

same flow front velocities at different mold temperatures.

3.1.4 Conclusion

For the alternate flow marks, the effect of polymer rheology, injection speed,

mold geometry, melt temperature, mold temperature, holding pressure, injection

65

pressure, and mold surface coatings on the appearance of the alternate flow marks was

studied. It was found that a polymer with the highest dynamic viscosity, elastic

modulus, first normal stress difference, transient extensional viscosity, and the longest

relaxation time exhibited the alternate flow marks. For the alternate dull and shiny flow

marks, flow front velocity is a very important variable. The flow marks occurred above a

critical wall shear stress, but disappeared at high injection speeds. For the wavelength

and the width of the flow marks, mold geometry or mold temperature had an effect.

However, melt temperature did not have much effect. The flow marks could be reduced

by one or more of the following factors: high injection speed, high melt or mold

temperature, mold surface coatings, and/or changing molecular weight or its distribution.

It was found that there was no difference between the crystallinity of dull regions and

shiny regions. The melt in dull regions was slightly oriented while the melt in shiny

regions was highly oriented. It was also found that coating these surfaces could not

prevent the occurrence of the flow marks, although it could alleviate them. Slip was not

the cause of the generation and disappearance of the alternate flow marks. The

generation of the flow marks could be explained by an entry viscoelastic flow instability.

3.2 SYNCHRONOUS DULL AND GLOSSY FLOW MARKS

3.2.1 Introduction

Several types of flow marks may occur during polymer melt injection molding

processes, such as alternate dull and glossy flow marks and synchronous dull and glossy

66

flow marks. Flow marks cause aesthetic defects on the surface of molded parts, and are

very difficult to cover with paints. Because they are not well understood, much attention

has been paid to the flow marks in recent years. Although alternate dull and shiny flow

marks [Yokoi, 1994b; Chang, 1996a; Chang, 1996b; Hobbs, 1996; Heuzey, et al., 1997;

Hamada and Tsunasawa, 1996; Dharia, 1999; Bulters and Schepens, 2000; Grillet, et al.,

2000; Charmeau, et al., 2000; Xu and Koelling, 2001; Jayaraman, 2002] and wavelike

flow marks [Tredoux and Satoh, 1999; Tredoux, et al., 2000; Yokoi, et al., 1994a;

Yoshii, et al., 1993; Yoshii, et al., 1996; Lee and Mills, 1994] have been studied in

literature, little work has been undertaken to synchronous flow marks [Yokoi, et al.,

1994c; Salamon, et al., 1998]. This type of flow marks is characterized as repeated dull

and glossy regions where a dull/glossy zone on one side corresponds to a dull/glossy

zone on the other side, as shown in Fig. 3.29.

Yohoi [Yokoi, et al., 1994c] found that the gate shapes and mold surface quality

had a great effect on the generation of flow marks and the flow marks varied

dramatically with the front flow velocity. At a higher melt temperature, flow marks

become thinner. At the melt temperature of 240ºC, flow marks as well as pressure

variation did not occur. They explained that during the filling process, the gate pressure

was increased, while the melt velocity was decreased at the flow front and the melt was

cooled down. On the other hand, the gate was frozen and the flow resistance was

increased. Therefore, the melt at the flow front was accelerated with the release of the

high gate pressure, and thus the resin near the flow front underwent cooling.

Consequently, the transcription precision decreased in the subsequent fountain flow

67

process. Then the flow marks were formed. In injection molding with a center-gate,

halos similar to flow marks with synchronous dull and glossy regions were formed

[Salamon, et al., 1998]. It was found that the temperature gradient was the cause of the

formation of the halos. It was also shown that with the increase of injection rates, the

halos became more prominent and the diameter of the halos became larger.

In this paper, we study the effect of operating parameters and mold surface

coatings on flow marks of different polymer melts. Possible correlation between gross

melt fracture in extrusion and synchronous dull and glossy flow marks in injection

molding is discussed, and a possible mechanism is proposed.

3.2.2 Experimental

Molding experiments were conducted on a Sumitomo SG M-HP 180-ton

injection molding machine. The materials used were two types of high-density

polyethylene, named HDPE1 and HDPE2. Two rectangular molds were employed with

different thicknesses (1 and 5.1 mm). The edge gates were used with a thickness of 0.5

mm for the thin mold and 2.5 mm for the thick mold. The length and width of the mold

channel was 150 and 51 mm, respectively. The melt temperature was 180, 210 and

240°C, while the mold temperature varied from 20 to 70°C. The complex viscosity,

storage and loss modulus, and first normal stress difference were measured by a

Rheometrics RMS 800. A tensile tester, Instron 8511, was used to measure the

extensional viscosity at 100°C, based on the standard ASTM test. The samples were

standard tensile bars with 13 mm in the narrow-section width, 57 mm in total length, and

68

3.2 mm in thickness. To obtain the constant strain rate, one needs to program the Instron

machine to follow the exponential type increase of sample length. Dynamar 9613 (a 3M

product), a fluorocarbon elastomer, was used as a coating agent. Its dilute acetone

solution, ca. 1%, was coated on hot surfaces and then the solvent was allowed to

evaporate.

A Differential Scanning Calorimeter from TA Instruments, DSC 2920, was used

to measure the crystallinity of dull and shiny regions. The sample was scanned from 30

to 200°C at the rate of 10°C/min. A Scanning Electron Microscopy, Philips XL 30, was

employed to observe the morphology of dull and shiny regions. An optical profilometer,

Wyko NT330, was used to measure the roughness of the dull and shiny regions. To

exam the melt fracture phenomena, a two-stage single-screw extruder (Rheomex 252p)

from Haake was applied. The screw has a diameter of 3/4 inches and a length to

diameter ratio (L/D) of 25. A capillary die with 1.2 mm in diameter and 12 mm in

length was used. The temperature profile from front zone to the die was 100°C /125°C

/145°C /145°C. The flow rate was calculated by dividing the measured sample weight

collected by the time duration.

Because it is very difficult to estimate the wall shear stress in molding filling, C-

MOLD 2000 was used to simulate filling molds. First the geometry was built, then the

mesh was generated. In the simulation, processing parameters, such as shot size, V/P

switch pressure, holding pressure, holding time, cooling temperature and cooling time,

were the same as those in the real injection molding processes. After the simulation, the

wall shear stresses at the center of flow front and gates were read.

69

3.2.3 Results and Discussion

3.2.3.1 Rheological Characterization

The complex viscosity of HDPEs was measured at 180, 200 and 220°C. Fig.

3.30 shows the complex viscosity at 180°C. It was found that the complex viscosity

decreased with an increase in frequency. Fig. 3.31 shows the storage modulus and loss

modulus at 200°C. Fig. 3.32 shows the first normal stress difference N1 versus shear

rate at 180°C. It was found that HDPE1 had a larger complex viscosity, elastic modulus,

viscous modulus, and first normal stress difference than HDPE2. Fig. 4.33 shows that

the extensional viscosity vs. time at the strain rate of 0.001. It was found that HDPE1

had a larger extensional viscosity at the same strain rate.

3.2.3.2 Injection Molding Experiment

It was found through the experiment trials that both HDPEs exhibited

synchronous flow marks at certain processing conditions. The flow marks were

generally in the phase between the top and the bottom.

Flow mark description

The flow marks occurring were characterized as synchronous dull and shiny

regions. Flow marks occurred in the thin mold only when the flow front velocity was

large. The flow marks did not occur in the thick mold. The flow marks did not occur

immediately after the gate. With an increase in the injection speed, flow marks became

70

more pronounced and continuous. When the injection speed was further increased, flow

marks became more continuous and it was difficult to distinguish different regions. The

width of the dull regions changed with the velocity of the flow front. Fig. 3.34 shows a

typical sample of flow marks for HDPE2.

Effect of operating conditions on flow marks

It was found that flow mark patterns changed as the injection speed increased.

Fig. 3.35 shows the effect of flow front velocity on the wavelength for HDPE2. It was

found that for the thin mold, the wavelength decreased with the increase of the flow

front velocity. Furthermore, the wavelength is shorter at a lower melt temperature;

nevertheless, at a higher melt temperature, the wavelength is not affected by the melt

temperature. Fig. 3.36 shows that for HDPE2 the lower the mold temperature, the

longer the wavelength. It was also found that with an increase of the mold temperature,

the flow marks were dimmer.

For the synchronous flow marks of HDPE2, the width of the dull regions was

usually very narrow, around 1-3 mm at the flow front velocity ranging from 0.4-0.9 m/s.

At a higher flow front velocity, the dull and shiny regions became irregular and mixed

together, making it very difficult to distinguish different regions. However, it was

clearly observed that the width increased with an increase of the flow front velocity.

It was found that flow marks occurred above a certain flow front velocity, Vcri. It

was further found that the mold temperature almost had no effect on Vcri. However, Vcri

increased as the melt temperature increased, as shown in Fig. 3.37. It was also found in

71

the experiment that the flow marks were less visible as the mold temperature increased.

The flow marks were almost invisible when the mold temperature was larger than 85°C.

Mold surface coating

The effect of the coating on the surfaces of the mold or gate was studied. It was

found that the coating on these surfaces could not prevent the occurrence of flow marks,

although it could alleviate the flow marks and make them dimmer. Another interesting

phenomenon is that coating on the mold surfaces did not change the Vcri, implying that

slip is not the cause of the synchronous flow marks. The reason is that coating on the

mold surface reduces the critical shear stress where the slip occurs, thus decreasing the

Vcri where the slip is triggered.

From the above discussion, we can see that for the wavelength and the width of

flow marks, injection speed is the most important factor and mold thickness plays a role.

Changing the melt temperature and mold temperature has an effect on the flow marks.

3.2.3.3 Morphology and Crystallinity

The DSC experiment showed that there was no difference observed in the

cystallinity between the dull and shiny regions for both HDPEs. From the SEM, it was

found that the polymer in the shiny region was highly oriented, but the polymer was

slightly oriented in the dull region, as shown in Fig. 3.38. This is in agreement with our

previous results for alternate flow marks and other researchers’ results [Salamon, et al.,

1998]. The measured average roughness by optical profilometer was smaller in shiny

72

regions than in dull regions, as shown in Table 3.4. The reported average roughness is

the average value of 5 randomly selected positions.

3.2.3.4 Extrusion

The HDPEs were extruded at the die temperature 145°C. It was found that above

a certain wall shear stress, sharkskin melt fracture occurred for both HDPEs. At a higher

wall shear stress, spurt flow instability occurred. At a still higher wall shear stress, gross

melt fracture occurred. The extrudate irregularity was helical. The flow curve of

HDPE2 is shown in Fig. 3.39. The average pressure was used to calculate the wall shear

stress when pressure oscillation occurred. The wall shear stress was estimated by

DL

P

/4

∆ without the Bagley correction, where ∆P is the pressure drop in the die, L is the

die length, and D is the diameter of the die. The apparent shear rate was calculated by

3

32

D

Q

π, where Q is volumetric flow rate. Th experiment showed that the critical wall

shear stress for the onset of sharkskin is about 0.24 MPa, and the critical wall shear

stress for the onset of the helical irregularity is about 0.51 MPa. The typical examples of

smooth surface, sharkskin, spurt flow, and helical melt fracture are shown in Fig. 3.40.

3.2.3.5 Simulation

To obtain wall shear stress during filling of the spiral molds, a simulation was

run on C-MOLD 2000. The critical wall shear stresses at the middle of the gate were

73

obtained for HDPE2 where the flow marks began to form. The processing parameters

and Vcri were determined from the injection molding experiments. Fig. 3.41 shows the

critical wall shear stress at the middle of the gate at different melt temperatures. It was

found that the wall shear stresses were very close before the F/P switch. That means the

flow marks start to form at the same wall shear stress 0.84 MPa at the gate at different

melt temperatures. Fig. 3.42 shows the critical wall shear stress at the middle of the gate

vs. the filling percentage at different mold temperatures. It shows that for the same

resin, the wall shear stress generally did not change much at different mold temperatures.

The decreasing sections of the curves in Figs. 3.41 and 3.42 were the pressure holding

stages. Short shots happened for the samples. From the simulation, it was found that

flow marks started at the same critical wall shear stress independent of melt temperature

and mold temperature.

3.2.3.6 Mechanism

The extrusion instability is associated with the appearance of distortion on the

extrudate surface, sometimes accompanied by oscillatory flow. For linear polymer melts

such as LLDPE and HDPE, when the shear stress reaches a critical value, the surface

becomes rough and wavy, and sharkskin occurs. At a higher stress, slip-stick or spurt

flow occurs. At a still higher stress, a transition region may occur where the surface is

relatively smooth with long-wavelength distortion. At much higher stress, gross or wavy

distortion occurs [Denn, 2001]. This is in agreement with our extrusion experimental

results. Although there is a disagreement about the cause of the origin of gross melt

74

fracture, most researchers agree that entry instability causes the melt fracture [Piau and

Agassant, 1996; Piau, et al., 1990; Den Otter, 1970]. The instability is also affected by

various properties, such as polymer structure, geometry of die entry, melt temperature,

and die temperature [Piau and Agassant, 1996].

For the generation of vortices and gross melt fracture, a detailed introduction can

be found in Section 3.1.3. For viscoelastic fluids, a corner vortex may occur at a low

flow rate before a contraction. The corner vortex zone is a dead zone and does not

interact with the outside fluid. The formation of vortices may be due to the increasing

extensional viscosity with the deformation rate and/or the shear-thinning effect [Denn

Otter, 1970; Cpgswell, 1972]. For some viscoelastic fluids, as a flow rate is increased, it

grows inward toward lip [Yesilata, et al., 1990]. The upstream flow is steady in this

stage. At a very high flow rate, it grows upstream, and the corner vortex fluctuates and

makes the flow field entirely unstable. For some other viscoelastic fluids, as the flow

rate is increased, two types of vortices, corner vortex and lip vortex, coexist. As the

flow rate is increased, the corner vortex and lip vortex recirculating areas expand [Piau

and Agassant, 1996; Yesilata, et al., 1999]. Then the lip vortex gradually develops and

invades the corner vortex, and finally generates a single area of recirculation. At a still

higher flow rate, the flow becomes unstable and the vortex pulsates or rotates, causing a

global change of flow structure [Boger, et al., 1986; Rothstein and McKinley, 2001]. It

was found that the development of upstream instabilities governed the appearance of the

extrudates and the helix pitch. The melt fracture occurs when the vortex is unstable.

The amplitude and frequency of pulsation increases with the pressure [Piau and

75

Agassant, 1996]. Usually the surface distortion and the frequency of the vortex

pulsation are identical.

In short, vortices may form before a contraction, and unstable vortices and gross

melt fracture are closely related. In fact, the process that polymer melts experience in

injection molding is similar to that of extrusion, as shown in Fig. 3.18. That is, the

polymer melt meets a contraction and experiences high shear stress at the die or gate,

then the polymer melt leaves the die or gate and the polymer chains relax. Thus, for

polymer melt experienced injection molding, we could logically expect that a vortex may

form and an instability may happen at the entry when the flow rate is high. The

oscillating entry instability can propagate and affect the downstream flow. Thus

oscillating or pulsating flow may also occur in the mold, and the different history of

heating and shearing which the melt experiences generates flow marks. The different

flow marks, alternate dull and glossy flow marks and synchronous dull and glossy flow

marks, may be due to two different types of vortex instabilities, oscillating or pulsating

instability. Furthermore, the pulsating instability probably results in synchronous flow

marks. The pulsating flow makes the flow front velocity change periodically from low

to high, and it also changes the flow front melt temperature and shear stress periodically,

as shown in Fig. 3.43. Thus, this periodical changing generates synchronous flow marks

because the top and bottom are identical, i.e. in phase. Our experiment showed that both

HDPEs exhibited helical gross melt fracture at a high flow rate, so it is not surprising

that HDPEs exhibited flow marks. In fact, synchronous flow marks of HDPE2 started to

occur at the same wall shear stress independent of melt and mold temperature, implying

76

that they have the same characteristic as gross melt fracture and may have the same

origin of abnormal appearance ⎯ the entry instability. The reason is that entry

instability for the generation of gross melt fracture in extrusion occurs at the same

critical wall shear stress level and does not changed with the die temperature

[Kazatchkov, et al., 1995].

This mechanism could explain our experimental results of flow marks. It was

found that the frequency of the flow marks increased with the increase of flow front

velocity, as shown in Fig. 3.44. The frequency was calculated by dividing the flow front

velocity by the wavelength. The trend of frequency is in a reasonable range compared to

the frequency of vortices of gross melt fracture in extrusion [Denn Otter, 1970]. We

believe that entry viscoelastic instability accounts for the synchronous dull and glossy

flow marks.

3.2.4 Conclusion

For synchronous dull and glossy flow marks, the effect of operating parameters,

mold geometry, and mold surface coatings on the flow marks was studied. Synchronous

dull and glossy flow marks occurred above a certain flow front velocity. It was also

found in the experiment that the flow marks were less pronounced as the mold

temperature increased. It was found that there was no difference between the

crystallinity of dull and shiny regions. However, the polymer was highly oriented in

shiny region while it was slightly oriented in dull regions. It was also found that mold

surface coatings did not eliminate the flow marks. Mold surface coatings scarcely

77

changed the Vcri, meaning that slip was not the cause of the generation of the flow

marks. Extrusion experiments showed that helical gross melt fracture occurred for both

HDPEs. Finally, it was proposed that entry viscoelastic instability was the reason for the

generation of the synchronous flow marks.

78

PP-A PP-B PP-C PP-D

Relaxation time λ (s) 0.223 0.447 1.382 0.548

Zero viscosity ηo (Pa.s) 915 5446 30166 7445

ηs (Pa.s) 182 619 1500 787

Table 3.1 Relaxation time and zero viscosity at 200°C

79

Polymer PP-A PP-B PP-C PP-D

Mν 128,000 142,000 121,000 164,000

Table 3.2 Viscosity-molecular weight

80

Sample 1

(nm)

Sample 2

(nm)

Sample 3

(nm)

Sample 4

(nm)

Sample 5

(nm)

Shiny Dull Shiny Dull Shiny Dull Shiny Dull Shiny Dull

495.9 692.4 387.1 571.1 435.8 504.4 530.4 571.2 336.9 344.7

Table 3.3 Average roughness of the dull and shiny regions

81

Sample 1

(nm)

Sample 2

(nm)

Sample 3

(nm)

Sample 4

(nm)

Sample 5

(nm)

Shiny Dull Shiny Dull Shiny Dull Shiny Dull Shiny Dull

453.8 514.1 422.0 480.6 398.8 484.8 390.8 467.1 356.3 486.3

Table 3.4 Average roughness of the dull and shiny regions

82

Fig. 3.1. Alternate dull and glossy regions.

λ

Dull regions are out of phase onthe top and the bottom

Dull region

83

Fig. 3.2. Comparison of viscosity vs. frequency at 200°C.

1.E+02

1.E+03

1.E+04

1.E+05

1.E-01 1.E+00 1.E+01 1.E+02

Frequency (1/s)

Vis

cosi

ty (

Pa.

s)

PP-A

PP-B

PP-C

PP-D

84

Fig. 3.3. Comparison of complex viscosity of PP-C at 180, 200, and 220°C.

1.E+02

1.E+03

1.E+04

1.E+05

1.E-01 1.E+00 1.E+01 1.E+02

Frequency (1/s)

Vis

cosi

ty (P

a.s)

180°C

200°C

220°C

85

Fig. 3.4. Comparison of elastic and viscous modulus at 200°C.

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E-01 1.E+00 1.E+01 1.E+02

Frequency (1/s)

Mod

ulus

G' a

nd G

" (P

a)

PP-A G'PP-A G"

PP-B G'PP-B G"PP-C G'PP-C G"

PP-D G'PP-D G"

86

Fig. 3.5. First normal stress difference vs. shear rate at 200°C.

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

0.001 0.010 0.100 1.000 10.000

Shear rate (1/s)

N1

(PA

)

PP-A 200°C

PP-B 200°C

PP-C 200°C

PP-D 200°C

87

Fig. 3.6. The first normal stress difference of PP-C vs. shear rate at 180, 200, and 220°C.

10

100

1000

10000

0.001 0.010 0.100Shear rate (1/s)

N1

(Pa)

180°C

200°C

220°C

88

Fig. 3.7. Transient extensional viscosity at 130°C.

1.E+07

1.E+08

1.E+09

0.1 1.0 10.0 100.0Time (s)

Ext

ensi

onal

vis

cosi

ty (

Pa)

PPAPPBPPCPPD

89

Fig. 3.8. Determination of relation time by one-mode Giesekus model.

1.E-02

1.E-01

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.00E-02 1.00E-01 1.00E+00 1.00E+01 1.00E+02 1.00E+03

Reduced frequency ωα T (1/s)

η',

2 η"/

ω

n'

2n"/w

η'

η ' Giesekus

2η"/ω

2η"/ω Giesekus

90

a: 0.02"/s b: 0.1"/s

c: 0.5"/s d: 2"/s

e: 4"/s f: 6"/s

Fig. 3.9. Flow marks of PP-C at different injection speeds.

91

Fig. 3.10. A typical example of the alternate dull and shiny flow marks.

92

Fig. 3.11. Effect of melt temperature on the wavelength λ.

0

2

4

6

8

10

12

14

16

18

0 2 4 6Flow front velocity (m/s)

Wav

elen

th

(mm

)

Tmelt=190°C

Tmelt=225°C

Tmelt=260°C

Tmold=22°CMold thickness: 1 mm

93

Fig. 3.12. Effect of mold temperature on the wavelength λ.

0

2

4

6

8

10

12

14

16

0 0.5 1 1.5Flow front velocity (m/s)

Wav

elen

gth

(m

m)

Tmold=22°C

Tmold=50°C

Tmold=80°C

Tmelt=190°C Mold thickness: 1 mm

94

Fig. 3.13. The effect of mold thickness on the wavelength λ.

0

5

10

15

20

25

30

35

40

0 0.5 1 1.5

Flow front ve locity (m/s)

Wav

elen

gth

(m

m)

Thickness 1 mmThickness 5.1 mm

Tmelt=190°C

Tmold=22°C

95

Fig. 3.14. Effect of melt temperature on the width of the flow marks.

0

1

2

3

4

5

6

7

8

9

0 2 4 6

Flow front velocity (mm/s)

Wid

th o

f fl

ow m

ark

s (m

m)

Tmelt=190°CTmelt=225°CTmelt=260°C

Tmold=22°CMold thickness: 1 mm

96

Fig. 3.15. Effect of mold temperature on the width of the flow marks.

0

1

2

3

4

5

6

7

8

9

0 0.5 1 1.5Flow front velocity (mm/s)

Wid

th o

f fl

ow m

ark

s (m

m)

Tmold=22°CTmold=50°CTmold=85°C

Tmelt=190°CMold thickness: 1 mm

97

Fig. 3.16. The effect of mold thickness on the width of the flow marks.

0

5

10

15

20

25

30

35

0 0.5 1 1.5Flow front velocity (m/s)

Wid

th (

mm

)

Thickness 1 mmThickness 5.1 mm

Tmelt=190°CTmold=22°C

98

Fig. 3.17. The starting of the flow marks, Vcri vs. melt temperature.

0

0.05

0.1

0.15

0.2

0.25

150 200 250 300

Melt temperature (oC)

Vcr

i (m

/s)

T mold=22oC

99

Fig. 3.18. Effect of melt temperature on the transition velocity, Vtrans.

0

1

2

3

4

5

6

7

8

9

10

150 200 250 300Melt temperature (oC)

Tra

nsit

ion

velo

city

(m

/s) T mold=22oC

100

Fig. 3.19. Flow mark zone of PP-C.

1.E-02

1.E-01

1.E+00

1.E+01

150 200 250 300

Melt temperature (oC)

Tra

nsit

ion

& c

riti

cal v

eloc

ity

(m/s

)

Tmold=22°C

Flow mark zone

Vtran

Vcri

101

(a) Shiny region

(b) Dull region

Fig. 3.20. Morphology of surfaces of dull and shiny regions.

102

(a) Low wall shear stress

(b) High wall shear stress

Fig. 3.21. Gross melt fracture of the PP in extrusion.

103

Fig. 3.22. The wall shear stress versus apparent shear rate in the extrusion.

0

0.05

0.1

0.15

0.2

0.25

1.E+01 1.E+02 1.E+03 1.E+04

Apparent shear rate (1/s)

Wal

l sh

ear

stre

ss (

MP

a)

104

Fig. 3.23. Wall shear stress vs. percentage filled in the thin spiral mold.

0

0.05

0.1

0.15

0.2

0.25

0 20 40 60 80 100Fill%

Sh

ear

stre

ss(M

pa)

PP-APP-BPP-CPP-D

105

Fig. 3.24. The critical wall shear stress at the middle of the gate at different melt

temperatures.

0

0.1

0.2

0.3

0.4

20% 30% 40% 50% 60% 70% 80% 90% 100%

Fill ing Percentage

Wal

l She

ar S

tres

s (M

Pa)

Tmelt=190°C

Tmelt=225°C

Tmelt=260°C

106

Fig. 3.25. The critical wall shear stress at the middle of the gate at different mold

temperatures.

0

0.1

0.2

0.3

20% 30% 40% 50% 60% 70% 80% 90% 100%

Filling Percentage

Wal

l She

ar S

tres

s (M

Pa)

Tmold=22°C

Tmold=55°C

Tmold=80°C

107

Fig. 3.26. The similarity between extrusion and injection molding processes.

gate

die

mold

extrudate

runner

barrel

108

Fig. 3.27. Oscillating flow generates alternate flow marks.

Flow front

Flow direction

Cav

ity

thic

knes

s

gloss

dull

dull

gloss

normal

normal

Flow front

Flow direction

Cav

ity

thic

knes

s

gloss

dull

dull

gloss

normal

normal

109

Fig. 3.28. Frequency of the flow marks versus flow front velocity.

0

10

20

30

40

50

60

70

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Flow front velocity (m/s)

Fre

quen

cy (

1/s)

110

Fig. 3.29. Synchronous dull and glossy regions.

λ

Dull regions are on the phaseon the top and the bottom

Dull region

111

Fig. 3.30. Comparison of viscosity vs. frequency at 180°C.

1.E+02

1.E+03

1.E+04

0 1 10 100Frequency (1/s)

η∗

(Pa.

s)

HDPE1

HDPE2

112

Fig.3.31. Comparison of Elastic and viscous modulus at 180°C.

1.E+02

1.E+03

1.E+04

1.E+05

0.1 1.0 10.0 100.0Frequency (1/S)

G',G

" (P

a.s)

HDPE1 G'HDPE1 G"HDPE2 G'HDPE2 G"

113

Fig. 3.32. First normal stress difference vs. shear rate at 180°C.

1.E+00

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

0.1 1 10 100Shear rate (1/s)

N1

(Pa)

HDPE1

HDPE2

114

Fig. 3.33. Extensional viscosity vs. time at 100°C.

1.E+07

1.E+08

1.E+09

1.E+10

0.1 1.0 10.0 100.0 1000.0

Time (s)

Ext

ensi

onal

vis

cosi

ty (

Pa)

HDPE1

HDPE2

115

Fig. 3.34. Synchronous dull and shiny flow marks of HDPE2.

116

Fig. 3.35. Effect of melt temperature on wavelength.

0

1

2

3

4

5

6

7

8

9

10

0.2 0.4 0.6 0.8 1Flow front velocity (m/s)

Wav

elen

gth

(m

m)

Tmelt=180°CTmelt=210°CTmelt=240°C

Tmold=20°CMold thickness: 1 mm

117

Fig. 3.36. Effect of mold temperature on wavelength.

0

1

2

3

4

5

6

7

8

9

10

0.2 0.4 0.6 0.8 1Flow fron t ve loci ty (m /s)

Wav

elen

gth

λ (m

m)

Tmold=20°CTmold=50°C

T melt=210°CMold thickness: 1 mm

118

Fig. 3.37. Effect of melt temperature on Vcri.

0

0.2

0.4

0.6

150 200 250Me lt te m pe ratu re (oC )

Vcr

i (m

/s)

119

(a) Dull region

(b) Shiny region

Fig. 3.38. Morphology of dull and shiny region of HDPE2.

120

Fig. 3.39. Flow curve of HDPE2 in extrusion.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1.E+01 1.E+02 1.E+03 1.E+04 1.E+05

Apparent shear rate (1/s)

Wal

l she

ar s

tres

s (M

Pa)

121

Fig. 3.40. Different extrudate irregularities at different wall shear stresses.

122

Fig. 3.41. Critical wall shear stress vs. percentage filled at different melt temperatures.

0

0.2

0.4

0.6

0.8

1

1.2

50% 60% 70% 80% 90%

Filling Percentage

Wal

l S

hea

r S

tres

s (M

Pa)

Tmelt=180°C

Tmelt=210°C

Tmelt=240°C

123

Fig. 3.42. Critical wall shear stress vs. percentage filled at different mold temperatures.

0

0.2

0.4

0.6

0.8

1

1.2

50% 55% 60% 65% 70% 75% 80% 85%

Filling Percentage

Wal

l S

hea

r S

tres

s (M

Pa)

Tmold=20°C

Tmold=50°C

Tmold=70°C

124

Fig. 3.43. Pulsating flow generates synchronous flow marks.

Flow front

Flow direction

Cav

ity

thic

knes

s

gloss

dull

dull

gloss

normal

normal

fast slownormal

Flow front

Flow direction

Cav

ity

thic

knes

s

gloss

dull

dull

gloss

normal

normal

fast slownormal

125

Fig. 3.44. Frequency of flow marks vs. Flow front velocity.

0

20

40

60

80

100

120

140

160

180

0 0.2 0.4 0.6 0.8 1Flow front velocity (m/s)

Fre

qu

ency

(1/

s)) Tmelt=180°C

Tmelt=210°CTmelt=240°C

Tmold=20°CMold thickness: 1 mm

126

CHAPTER 4

EXPERIMENT WITH MICRO-FEATURES AND IMPROVEMENT OF

SIMULATION ACCURACY DURING THIN-WALL INJECTION MOLDING

4.1 THIN-WALL INJECTION MOLDING WITH MICRO-FEATURES

4.1.1 Introduction

Injection molding of thermoplastics with micro-features is a new field in thin-

wall applications. In recent years, the fabrication of polymer-based micro-components

for optical and biomedical applications has been given increasing attention in industry

and academia [Yu, et al., 2004b]. Polymer materials are favored because of their low

cost, good biocompatibility, high optical clarity, and high impact strength compared with

silicon or glass. Micro-injection molding has the potential for economical mass-

production. It usually combines various lithography techniques and injection molding

[Weber and Ehrfeld, 1999]. Two types of micro-parts are available: micro-sized parts

and regular-sized parts with micro-features. Micro-injection molding (MIM) is the

injection molding of plastic parts with structure dimensions in the micron or sub-micron

range. The micro-features can be considered “very” thin-wall parts. The replication of

127

micro-features is an important issue and depends greatly on the size, aspect ratio and

covered area [Weber and Ehrfeld, 1999]. Furthermore, it is a challenge to simulate

micro-injection molding processes. It has been shown that standard injection molding

packages cannot describe all of the effects in micro-injection molding [Kenmann, et al.,

20002; Yu, et al., 2002]. This study focuses on thin-wall injection molding with micro-

features by experiment and numerical simulation. The filling lengths in microchannels

are simulated and compared with experimental results.

4.1.2 Experimental

A high-speed and high-pressure injection-molding machine, Sumitomo SG 180

M-HP, was used in our experiment. Two rectangular molds were employed. The mold

cavity contained not only the base plate but also the microchannels. The main lengths of

the two molds were 203 mm and 72 mm, respectively. The long rectangular thin-wall

mold was 2 mm in thickness, 203 mm in length and 50.8 mm in width, as shown in Fig.

4.1. The distance from the last channel (channel B) to the end of the main flow is 135

mm for the long mold, as shown in Fig. 4.2. The corresponding distance for the short

mold is 4 mm, as shown in Fig. 4.2. An edge gate with 3 mm in width was used for the

main flow. A disk-like mold insert with a diameter of 508 mm was installed in the mold

base. Two micro mold inserts were tested. One mold insert, including top view and side

view, is shown in Fig. 4.3. The mold insert includes six microchannels made with wire-

EDM. There are three separate microchannels and the other three are next to each other

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with a distance of 100 micrometers. All channels are 500 µm deep and 100 µm wide,

giving an aspect ratio of 5. The detailed structure of a microchannel from SEM is shown

in Fig. 4.4. Another mold insert has similar geometry but smaller width of

microchannels. The channels are 250 µm deep and 50 µm wide, giving an aspect ratio

of 5 too. Two pressure sensors made by Kistler were mounted at the position right

before and after the insert, respectively. The data acquisition system was built based on

the data acquisition board from Keithley.

The materials used were a semi-crystalline polymer, polypropylene (PP, Inspire

C703-35U, Dow Chemical), and an amorphous polymer, poly (methyl methacrylate)

(PMMA, PL 150, Plaskolite). The melt temperature was 240°C for PMMA and

240/260°C for PP. The mold temperature was 25 and 80°C for both materials. The

holding pressures were set at 0 psi or 500 psi. The injection speed varied from 0.2 to 5

inch/s.

The complex viscosity, storage and loss modulus were measured by a

Rheometrics RMS 800. A Scanning Electron Microscope (SEM), the Philips XL 30,

was employed to observe the microchannels. An optical profilometer, Wyko NT3300,

was used to measure the filling length of the microchannels. The vertical-scanning

interferometry (VSI) mode was used to measure step heights by multiple wavelengths of

light. The profilometer basically uses the interference of light to determine the surface

shape and transmission properties. First a light source is split into two beams, then a

pattern of interferences or fringes is formed when the two beams are reflected from a test

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surface and a reference surface and join together. A series of fringe patterns are

generated when the test surface is scanned. The recorded fringe patterns can be mapped

[NDSU Center for Nanoscale Science and Engineering, 2003]. The non-contact Wyko

NT3300 features outstanding software and advanced automation for highly accurate,

three-dimensional surface topography measurements. Height can be measured from

Angstroms to millimeters at a resolution of 0.1 nm. The profile of an object is

determined using interferometry instead of a stylus. Hence, the instrument is ideal for

measuring micro-structure profiles because they can be measured without destroying

their structure.

4.1.3 Experimental Results

The dynamic viscosity of PP and PMMA was measured by a Rheometrics RMS

800, as shown in Figs. 4.5 and 4.6. It was found that PP and PMMA were typical shear

thinning thermoplastics. The parts were molded for PP and PMMA under different

processing conditions. It was found that demolding was easy when the filling length in

the microchannels was small. However, demolding was difficult when the filling in the

micro channels with the width of 100 µm was deeper than 150 µm for PMMA and 300

µm for PP. In the long mold, deeper filling could be observed in the adjacent channels

than in the separated ones, and the difference might be significant. This is due to a

reduced heat loss for the melt in adjacent microchannels. However, the filling lengths

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were almost the same in 3 separated channels. Fig. 4.7 shows a SEM picture of a

molded microstructure from PP.

The molded parts with 100 µm microchannels were examined after injection

molding with the optical profilometer, to determine the replication accuracy of micro-

features. The measured filling lengths in the separated microchannels in the long mold

against the main flow velocity for PMMA and PP are shown in Figs. 4.8 and 4.9,

respectively. The filling lengths are longer at a higher main flow velocity for both PP

and PMMA. The molding of the microchannels is similar to thin-wall injection

molding. A high injection speed is the most efficient way to increase the flow length. A

higher mold temperature results in a longer filling length due to less flow resistance.

Furthermore, higher holding pressure generates a somewhat longer filling length,

although the effect is not significant. PP can achieve longer filling lengths than PMMA.

A complete filling can be observed for PP at a high injection speed. It should be pointed

out that at the mold temperature of 25°C, the cavity volume was not totally filled and no

packing stage occurred. However, the filling length for PP reached 500 µm. It implies

that the microchannels may be completely filled simply in the filling stage by PP. The

filling lengths in 50 µm micro mold are shown in Figs. 10 and 11. It was found that PP

can completely fill the micro channels but PMMA can fill only less than about 50 µm.

That is, it is much more difficult to fill the microchannels when the size is scaled down.

PP is much easier to fill the microchannels than PMMA.

The effect of channel location was studied, as shown in Fig. 4.12. It was

observed that the filling lengths in channels A and B in the short mold are much longer

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than those in the long mold. Furthermore, the filling length in channel B is much longer

than in channel A in the short mold. However, there is not much difference between the

filling lengths in channels A and B in the long mold. The difference is that channel B is

much closer to the end of the mold cavity in the short mold than in the long mold, as

shown in Fig. 4.2. The recorded cavity pressure vs. filling time in the short mold and the

long mold is shown in Fig. 4.13. If we define the filling time at which the main flow

reaches the mold cavity end as tc, the pressure profile is the same before tc, and then the

pressure increases sharply in the short mold. In the short mold, more melt can be packed

into the channels and the filling lengths in channels A and B are longer than in the long

mold. Also in the short mold, the filling length in channel B is longer than in channel A

because the melt in channel B experienced a shorter cooling time. However, in the long

mold, the polymer melt needs a relatively much longer time to flow from channel B to

the end of the mold (135 mm), and the melt in both microchannels may have frozen

before the main flow reaches the mold cavity end (i.e. before the sharp pressure rise).

Therefore, the cooling time does not affect the filling lengths at different channel

locations. We define the time the polymer melt needs to advance from the channel

position to the end of the mold cavity as ∆t, representing the degree of melt freezing in

the microchannels. If we plot the dimensionless filling lengths (filling length/depth) vs.

Fourier Number α∆t/L2, the dimensionless filling lengths decrease with the increase of

Fo. All of the data merge on a single curve, covering both molds and a wide range of

main flow velocities, as shown in Fig. 4.14.

132

The effect of packing stage on filling lengths is shown in Fig. 4.15. When the

shot size is small (≤ 0.0305 m), the mold cavity is not totally filled and there is no

packing stage. When the shot size is equal or larger than 0.0307 m, the packing occurs.

Whether the packing stage occurred or not was judged by a steep increase of the

recorded cavity pressure profile and visual observation of short shots. It was found that

at the main flow velocity of 200 mm/s, the filling lengths are about 164 µm without the

packing stage at the melt temperature of 240°C, mold temperature of 25°C and zero

holding pressure; however, the filling length increases with an increase in shot size and

the filling length reaches 334 µm finally at the shot size of 0.0508 m. At the main flow

velocity of 37.5 mm/s, the filling length is about 70 µm without packing stage, but the

filling length is 200 µm with packing stage (shot size 0.0508 m). It implies that the

packing stage is very important in filling the microchannels. The effect of holding

pressure on filling lengths is shown in Fig. 4.16. It shows that the holding pressure has

some effect on filling lengths, but is not significant.

4.1.4 Simulation Results

Because the thickness of the base plate is very large compared to the

microchannels, the conventional midplane simulation using the Hele-Shaw

approximation may result in a large inaccuracy. Therefore, a 2D x-z plane simulation is

applied (x is the axial flow direction and z is the thickness direction). To save

computational cost, a hybrid model is selected and numerical codes are developed by

Liyong Yu. The cavity is divided into three regions: the upstream, the middle, and the

133

downstream region. The 1D Hele-Shaw equation is used in upstream and downstream

regions where the control volume/finite element method (CVFEM) is used to solve the

Hele-Shaw equation and the finite difference method (FDM) is used to solve the energy

equation. The 2D general momentum equation is used in the middle region where

(CVFEM) is used to solve the momentum and energy equations numerically. The hybrid

approach has 584 triangle elements and 40 1D elements. There are 21 layers in the

thickness direction. Detailed information can be found elsewhere [Yu, 2004a; Yu,

2004b].

A series of simulation were run in the long mold by Liyong Yu. Because the heat

transfer coefficient h is very difficult to determine, the melt/base plate wall interface heat

transfer coefficient h is assumed constant, h=25000 W/m2⋅K, and three different constant

melt/microchannel wall interface heat transfer coefficients are tested. Fig. 4.17 shows

that the filling lengths are greatly underpredicted for most injection speeds for PP at the

mold temperature of 25°C. This is because the heat transfers so quickly (h=25000

W/m2⋅K) that the melt near the wall freezes before the melt can enter into the

microchannel. If the main flow heat transfer coefficient is selected to be 2000 W/m2⋅K,

the polymer melt flows much deeper into the microchannel, as shown in Fig. 4.18.

Furthermore, the value of the melt/microchannel wall heat transfer coefficient also plays

an important role in predicting the filling length. It can be concluded that the heat

transfer coefficient is critical in the filling simulation of a mold with micro-features.

Next, a different boundary condition for heat transfer at the wall was further tested:

( )wmx TThq −=

134

where Tm is the gapwise mean temperature and hx is the variable local heat transfer

coefficient. hx is a function of the flow field and expressed by the local Nuselt number

Nux and the hydraulic diameter Dh [Shah and London, 1978]:

hxx DkNuh /=

25.00 )/( wbxx NuNu µµ=

⎪⎩

⎪⎨

⎧

>−−+

≤+−=

0.001 x* 245x*e0.4880x*)6.874 (1007.541

0.001 x* 0.4 1/31.233 (x*)0xNu

for

for

Pr)Re/(* hDxx =

where µb and µw are the bulk viscosity and the viscosity at the wall.

Using the variable heat transfer coefficient, the filling length of PP in the long

mold was predicted very well at mold temperatures of 25°C and 80°C, as shown in Fig.

4.19.

4.1.5 Conclusion

Thin-wall injection molding with micro-features was studied experimentally and

numerically. It was found that the filling lengths in microchannels are affected by

injection speed, mold temperature, and channel location. A high injection speed or high

mold temperature results in a longer filling length. Moreover, the filling lengths in the

microchannels increase with a decrease in the filling time flowing from the microchannel

to the mold cavity end. It can be concluded that the filling stage is important, the

135

packing stage is also important (especially in the short mold), and the holding stage is

not important in filling the microchannels with PP. It is more difficult to fill the smaller

microchannels. Furthermore, the filling lengths in the microchannels are simulated by a

hybrid simulation code with a combination of the momentum equation and the Hele-

Shaw model, and compared with experimental results. The code has fewer elements and

requires less computation time. The simulation shows that the filling lengths in

microchannels are sensitive to the heat transfer coefficients in the main flow cavity and

in the microchannel, and extra attention is needed to select the proper heat transfer

coefficient. By using a variable heat transfer coefficient, the filling length in the long

mold was predicted very well.

4.2 CAVITY PRESSURE AND ITS PREDICTION DURING THIN-WALL

INJECTION MOLDING

4.2.1 Introduction

Injection mold cavity pressure is one of the most important parameters in the

thin-wall injection molding process. It plays an important role in determining the

molded part quality and is a good indicator of injection machine control performance

[Angstadt, 2001; Dubay, 2001]. It not only indicates the material condition in the mold

but also affects the microstructure and part quality [Macfarlane and Dubay, 2000; Gao,

et al., 1996; Gao, et al., 1996]. Cavity pressure can affect part weight, dimensions,

cosmetics, gloss, warpage, shrinkage, etc. [Bozzelli and Cardinal, 1996]. Therefore, it is

136

very important to study the effect of injection operating variables and material properties

on the cavity pressure (gradient).

Computer aided engineering (CAE) programs are commonly used today to design

a part successfully, optimize the process, and troubleshoot [Kalnin and Zluhan, 1999].

The application of CAE has the potential to reduce overall production cost and improve

part quality. However, the injection molding process is very complicated and many

operating variables and physical properties affect the mold cavity pressure. Almost all

users would prefer better accuracy of CAE simulation [Ainoya and Amono, 2001].

During thin-wall injection molding (TWIM), the prediction error in cavity pressure from

CAE simulation may reach from 50% to more than 100% and the error increases as the

parts become thinner [Chen, et al., 2000]. This error may be due to certain assumptions

and simplifications. For example, the effect of pressure on viscosity is neglected

although it is important in high pressure thin-wall processes [Chen, et al., 2000; Amano

and Ainoya, 2000; Fasset, 1995; Mahishi, 1998]. It was found that neglecting the effect

of pressure on viscosity led to overprediction of cavity pressure, while neglecting the

juncture loss led to underprediction of nozzle pressure [Sherbelis and Friedl, 1996]. The

heat transfer coefficient in CAE packages, such as in C-MOLD and MoldFlow, is

usually taken to be a constant (default value 25,000 W/m2⋅K), but it changes with time

and operating variables. pvT-data also affect cavity pressure [Ainoya and Amono,

2001]. Cavity pressure drop was extremely overpredicted when the effect of pressure on

viscosity and juncture loss were not considered. However, Sridhar and Narh [1999]

found that the heat capacity and thermal conductivity had almost no effect on cavity

137

pressure. Another reason for the error of simulation is the lack of a high quality database

for polymers, such as heat conductivity and pvT data [Chen, et al., 2000].

In this chapter, the effect of pressure-dependent viscosity, heat capacity, heat

transfer coefficient, juncture pressure loss and pvT-data on cavity pressure and pressure

drop prediction will be studied, and the importance of each parameter will be evaluated.

Then the importance of each variable will be evaluated, and the method to improve the

prediction accuracy will also be discussed. The cavity pressure and pressure drop are

measured experimentally and compared. The study aims to improve simulation accuracy

and offer the guidance to reduce time and cost for expensive property testing.

4.2.2 Simulation

A rectangular mold with a mold thickness of 1 mm was used in the experiment,

as shown in Fig. 4.20. A representative amorphous polymer, polystyrene (PS), and a

representative semi-crystalline polymer, high-density polyethylene (HDPE), were

selected. The melt temperature was 230°C and 250°C, and the mold temperature was

60°C for the PS. The melt temperature was 300°C and 320°C, and the mold temperature

was 80°C for the HDPE. Actual molding experiments were performed on a Sumitomo

SG M-HP 180 ton injection molding machine. A data acquisition system and software

from Keithley Instruments were used to measure cavity pressure. Pressure transducers

were made by Kistler Instrument Co.

The simulation was run on a commercial FEM software, Moldflow 3.0. To

estimate the effect of each factor on cavity pressure, the Taguchi array of the simulation

138

is shown in Table 4.1. Five two-level factors were discussed: the heat capacity Cp, the

pressure-dependent viscosity ηp, the juncture loss ∆P, the heat transfer coefficient h, and

the specific volume v. Level 1 of the heat capacity was chosen as a constant heat

capacity, and level 2 of the heat capacity changed with temperature. Level 1 of the

pressure-dependent viscosity ηp neglected the effect of the pressure while level 2

included the effect of pressure. Level 1 of the juncture loss ∆P ignored the juncture loss

while level 2 considered it. Level 1 of the heat transfer coefficient used Moldflow’s

default value, 25000 W/m2⋅°C. Level 2 of the heat transfer coefficient used 1500

W/m2⋅°C according to our experience. Level 1 of the specific volume v did not include

the effect of pressure, while level 2 included effects of both temperature and pressure.

The temperature-dependent heat capacity was measured by a DSC, TA 2920, at

the heating rate of 3.33°C/s. The results are shown in Fig. 4.21.

The pvT modeling was described by a double-domain Tait equation [Chiang, et

al., 1991].

)]B(T)

PC ln([1ovv(T,P) −= (1)

where

vo(T)=b1m+b2m T if T>Tt (2)

vo(T)=b1s+b2s T if T<Tt (3)

B(T)=b3mexp(-b4m T ) if T>Tt (4)

B(T)=b3sexp(-b4s T ) if T<Tt (5)

139

Tt=b5+b6 P (6)

T =T-b5 (7)

For semi-crystalline HDPE, the additional term vt (T, P) is added for v (T, P)

which is well known as the modified Tait equation:

(T,P)tv)]B(T)

PCln([1ovv(T,P) +−= (8)

where vt (T, P)=0 if T>Tt (9)

vt (T, P)=b7 exp (b8 T - b9P) if T<Tt (10)

pvT data were given by the Moldflow database and the specific volumes are shown in

Figs. 4.22 and 4.23, respectively.

The pressure-dependent viscosity was modeled by the Cross-WLF equation

[Hieber, 1987] over a wide range of shear rates, as shown below. The parameter D3

characterizes the effect of pressure on the glass temperature T* and thus the viscosity.

]-n )*oη(/[1oηη

1

τ

γ&+= (11)

where )2

T*)(T1A exp (-1Doη T*TA −+

−= (12)

PDDT* 32 += (13)

PDAA 322 += (14)

140

The viscosity under high pressure was measured by a capillary rheometer, the

Rheomex 252p. The measured pressure drops were corrected by the Bagley correction.

Furthermore, the viscosity at low shear rates under the ambient pressure was measured

by a Rheometrics RMS 800. The viscosity for PS and HDPE is shown in Figs. 4.24 and

4.25, respectively, and the fit model parameters are shown in Table 4.2.

To consider juncture pressure loss, the Bagley correction constants C1 and C2

were chosen as Moldflow recommended. That is, C1=6.79×10-2 Pa-0.399 and C2=1.399

for HDPE, and C1=3.3×10-5 Pa-1.108 and C2=2.108 for PS.

4.2.3 RESULTS AND DISCUSSION

The simulation results were obtained for PS in the thin-wall injection molding

process. The importance of each factor is evaluated by analysis of variance (ANOVA)

[Roy, 2001]. The peak cavity pressure values and the percent influence at three different

injection speeds, 0.5, 3 and 20 inch/s, are shown in Table 4.3 when the melt temperature

is 230°C. It was found that the specific volume is the most important factor affecting the

peak cavity pressure, and its importance increases with an increase in injection speed. A

similar conclusion can be drawn when the melt temperature is 250°C, as shown in Table

4.4. It means that a large error may occur if the effect of pressure on the specific volume

is neglected and the property should be strictly measured. The discrepancy between the

cavity pressures without the effect of pressure on the specific volume and with the effect

of both pressure and temperature on the specific volume can be seen in Fig. 4.26.

141

Without considering the effect of the pressure on the specific volume, the simulation

predicts a higher peak cavity pressure and relatively lower holding pressure.

Two other important factors affecting the peak cavity pressure are the pressure-

dependent viscosity and the heat transfer coefficient. ANOVA shows that both the heat

transfer coefficient and the pressure-dependent viscosity are significant factors when the

injection speed is low. It also shows that the percent influence of the heat transfer

coefficient is higher than that of the pressure-dependent viscosity, as shown in Tables

4.3 and 4.4. However, our previous simulation [Xu and Koelling, 2003] showed that the

effect of pressure on the viscosity is relatively more important than deciding the proper

heat transfer coefficient when the injection speed is high at lower melt temperatures. It

implies that the percent influence of the heat transfer coefficient and the pressure

dependent viscosity depends on both melt temperature and injection speeds. The percent

influence of the heat transfer coefficient and the viscosity decreases with the increase of

injection speeds. By including the effect of pressure on the viscosity, a higher peak

cavity pressure and a lower holding pressure are predicted, as shown in Fig. 4.27. Using

h=1500 W/m2.°C predicts a lower peak cavity pressure and a holding pressure that is

lower at first and then higher, as shown in Fig. 4.28. However, these two parameters are

very difficult to measure. Sherbelis and Friedl also predicted lower cavity pressure when

the effect of pressure on viscosity was considered [Sherbelis and Friedl, 1996].

The least important factors considered here are the heat capacity and the juncture

loss. The percent influence is very small, as shown in Tables 4.3 and 4.4. From Figs.

4.29 and 4.30, it can be seen that the heat capacity and the juncture loss have almost no

142

effect in this case. However, Table 4.3 shows that the contribution of the heat capacity

to cavity pressure increases at high injection speeds, which is usually true in thin-wall

injection molding. For heat capacity, it is very difficult to get the “true” value because

the cooling rate is very fast in thin-wall injection processes, such that common

instruments cannot scan samples fast enough. At a higher melt temperature of 250°C,

the percent influence of each factor, as shown in Table 4.4, is similar as the melt

temperature of 230°C. Sridhar and Narh [1999] also found that thermal conductivity and

heat capacity had almost no effect on cavity pressure. Other researchers also found that

a tabulated heat capacity led to a slightly higher cavity pressure drop [Ainoya and

Amono, 2001].

The simulation results of peak cavity pressure for HDPE were also obtained. The

percent influence of each factor at two different melt temperatures, 300°C and 320°C, is

shown in Table 4.5. It was found that the specific volume and the heat transfer

coefficient are significant factors. The specific volume has the largest percent influence,

but pressure-dependent viscosity also has a relatively large percent influence compared

to the effect of the heat capacity and juncture loss.

The simulation implies that a large error may occur if the effect of pressure on

the specific volume and/or the viscosity is neglected, and/or the heat transfer coefficient

is not properly determined. These values should be carefully determined before running

simulation. The juncture loss and the heat capacity do not play a significant role in this

case. Thus full attention needs to be given to the specific volume, the pressure

dependent viscosity, and the heat transfer coefficient when the material property model

143

is selected for simulation, and less effort should be given in determining the heat

capacity and the juncture loss.

The maximum cavity pressure drops were simulated for PS. As shown in Tables

4.6 and 4.7, the percent influence of the heat transfer coefficient is the largest among the

five factors under study, so the most important factor affecting cavity pressure drop is

the heat transfer coefficient. Generally speaking, the percent influence of the viscosity

and the specific volume are high, and the juncture loss is not a significant factor.

Furthermore, it is interesting to note that the heat capacity is not a significant factor

when the injection speed is low, but its percent influence increases dramatically with an

increase in the injection speed. However, it shows that the percent influence of the

viscosity decreases with an increase in the injection speed. For the pressure drop of

HDPE, it was found that the heat transfer coefficient and the viscosity have a high

percent influence, as shown in Table 4.8. However, the heat capacity, the juncture

pressure loss, and the specific volume have almost no effect. The influence of the

material property model is apparently different for different polymer structures. This

also implies that the specific volume, the pressure dependent viscosity and the heat

transfer coefficient generally play important roles in the maximum cavity pressure drop

and these properties need to be carefully tested before running simulations.

Furthermore, the heat capacity may be important when a very high injection speed is

applied.

The actual cavity pressure and pressure drop were also measured. Fig. 4.31

shows the pressure profiles right after the gate and at the end of the cavity at an injection

speed of 76.2 mm/s. It was found that higher peak pressures both after the gate and at

144

the end of the cavity were detected when the melt temperature was lower, due to a higher

flow resistance. Moreover, the pressure drops more rapidly when the melt temperature is

lower because the melt cools down more rapidly. Fig. 4.32 shows the pressure profiles

right after the gate at the melt temperature of 230°C under different injection speeds. It

was found that a higher injection speed caused a lower peak cavity pressure. This agrees

with other researchers’ observations in the thin-wall injection molding process [Chen, et

al., 2000; Bozzelli, et al., 1997; Fierens and Mertes, 1998]. Moreover, the pressure

drops more slowly when the injection speed is higher, probably because of the short

cooling period at the filling stage and the high viscous heating. Fig. 4.33 shows the

pressure profiles at the end of the cavity under the melt temperature of 230°C under

different injection speeds. It was found that the peak pressure increases with an increase

in the injection speed, but the peak pressure drops a small amount when the injection

speed is further increased from 76.2 to 508 mm/s. Fig. 4.34 shows the measured cavity

pressure vs. time right after the gate at the low injection speed of 12.7 mm/s. The

simulation results from different material property models are also shown in this figure.

It was found that Moldflow predicts the filling stage fairly well, but there is a large

difference in the holding stage. It can be seen that neglecting the effect of pressure on

the specific volume caused a large difference in the peak cavity pressure. Furthermore,

the predicted pressure curve including the effect of pressure on the specific volume and

the viscosity (the solid triangles) is closest to the measured pressure curve at the holding

stage compared to other predicted curves. At a high injection speed of 508 mm/s,

Moldflow overpredicts the cavity pressure at both the filling stage and the holding stage,

as shown in Fig. 4.35. Neglecting the effect of pressure on the specific volume leads the

145

largest peak cavity pressure difference between the simulation and measurement, with a

difference of about 66%. The predicted pressure curve including the effect of pressure

on the specific volume and the viscosity (the solid triangles) is closest to the measured

pressure curve at the holding stage, compared to other predicted curves. Unlike the low

injection speed, Moldflow predicts the trend of the cavity pressure well at the holding

stage, but the predicted curve shifts upward from the experimental pressure curve. The

measured maximum cavity pressure drop is 38.9 MPa; however, the predicted pressure

drop is in the range of 46-50 MPa depending on the material property models used. It

can be seen that to obtain good simulation results, the effect of pressure on the specific

volume and the viscosity must be included, and the default value of the heat transfer

coefficient must be re-evaluated. At high injection speeds, good agreement cannot be

obtained regardless of the property models selected. The reasons are out of the range we

are considering. The possible reasons are: a discrepancy between the set operating

variables and the actual values the machine reached; an inefficiency in the property

models (e.g., a property measured under equilibrium is used to simulate a non-

equilibrium injection molding process); and/or the software itself due to simplifications.

4.2.4 CONCLUSION

For the thin-wall injection molding processes, it is very important to use proper

material property models when running simulations. It was found that the effect of

pressure on the specific volume is the most important factor to predict the peak cavity

pressure. The effect of pressure on the viscosity and the heat transfer coefficient is also

significant. The heat capacity and the juncture loss are relatively less important

146

compared to other factors considered here. It was also shown that the significant factors

are somewhat different to predict maximum cavity pressure drop. The heat transfer

coefficient is the most important factor, but in general the specific volume and the

viscosity are still important. At a high injection speed, the simulation overpredicted the

peak cavity pressure and the maximum cavity pressure drop, and good prediction cannot

be achieved. Further study is necessary to understand why this happens and how to

improve the simulation accuracy at very high injection speeds. However, the differences

between the measurements and the simulations are smaller at low injection speeds in our

case.

147

Table 4.1 Orthogonal array of the simulation

No. Cp η ∆P h v 1 1 1 1 1 1 2 1 1 1 2 2 3 1 2 2 1 1 4 1 2 2 2 2 5 2 1 2 1 2 6 2 1 2 2 1 7 2 2 1 1 2 8 2 2 1 2 1

Symbol 1 2 Cp Constant Variable η D3=0 PS: D3=1.51E-7

PE: D3=9.21E-8 ∆Pjuncture C1=0

C2=0 PS: C1=3.3E-5, C2=2.108 PE: C1=0.0679, C2=1.399

h 25,000 W/m2⋅K 1,500 W/m2⋅K v

No effect of pressure

Effect of pressure is considered

148

Table 4.2 Coefficients of Cross-WLF equation

Material τ∗ (Pa) N (-) D1 (Pa.s) D2 (K) D3(K/Pa) A1 (-) 2A (K)

PS 38264 0.177 2.72E13 368 1.51E-7 31.0 51.6

PE 2791 0.542 8.86E13 256 9.21E-7 26.0 51.6

149

Peak P (MPa) No. Cp ηp ∆P h v

0.5”/s 3”/s 20”/s 1 1 1 1 1 1 84.07 72.28 72.95

2 1 1 1 2 2 56.64 48.66 51.2

3 1 2 2 1 1 91.78 75.98 75.21

4 1 2 2 2 2 60.35 51.11 51.52

5 2 1 2 1 2 66.9 54.71 54.09

6 2 1 2 2 1 74.78 68.65 73.44

7 2 2 1 1 2 72.91 55.51 54.35

8 2 2 1 2 1 78.8 70.61 74.2

Percent Influence (%)

Injection speed Cp ηp ∆P h v

Significant

Factors

0.5”/s 0 5.64 0 25.77 67.28 η, h, v

3”/s 0 1.18 0.13 5.79 92.60 η, h, v

20”/s 0.32 0.12 0 0.48 98.71 v

Table 4.3 Relative influence of each factor on peak cavity pressure

at different injection speeds at 230°C

150

Percent Influence (%) Injection speed Cp ηp ∆P h v

Significant

Factors

0.5”/s 0 4.27 0 24.73 70.09 η, h, v

3”/s 0 0.89 0.03 6.32 92.59 η, h, v

20”/s 0.20 0.13 0.03 0.66 98.69 v

Table 4.4 Relative influence of each factor on peak cavity pressure

at different injection speeds at 250°C

151

Percent Influence (%) Temperatur

e Cp ηp ∆P h v

Significant

Factors

300°C 0 5.81 0 27.14 61.72

v, h

320°C 0 6.39 0 28.44 58.98

v, h

Table 4.5 Relative influence of each factor on peak cavity pressure

at different melt temperatures for HDPE at 0.5”/s

152

Percent Influence (%) Injection speed Cp ηp ∆P h v

Significant

Factors

0.5”/s 0 11.49 0 82.98 2.82 η, h

3”/s 0.07 7.96 0 88.94 0 h

20”/s 21.56 2.22 0.10 69.64 6.20 Cp, η, h, v

Table 4.6 Relative influence of each factor on maximum pressure drop

at different injection speeds at 230°C

153

Percent Influence (%) Injection speed Cp ηp ∆P h v

Significant

Factors

0.5”/s 0.06 8.99 0 86.78 2.55 η, h

3”/s 1.14 5.35 0 93.27 0 Cp, η, h

20”/s 21.56 1.74 0.32 67.54 7.40 Cp, h, v

Table 4.7 Relative influence of each factor on maximum pressure drop

at different injection speeds at 250°C

154

Percent Influence (%) Temperature

Cp ηp ∆P h v

Significant

Factors

300°C 0 8.11 0 88.23 0 h

320°C 0 7.48 0 87.94 0 h

Table 4.8 Relative influence of each factor on maximum cavity pressure drop

at different melt temperatures for HDPE at 0.5”/s

155

Fig. 4.1. The long rectangular mold base with a disk-like insert.

156

Fig. 4.2. The rectangular mold bases with a disk-like insert.

4 mm

135 mm A B

Long mold

Short mold

A B

157

Fig. 4.3. The disk-like mold insert which contains microchannels.

A A

View A-A

158

Fig. 4.4. SEM picture of the a microchannel.

159

Fig. 4.5. Dynamic viscosity of polypropylene.

1.E+02

1.E+03

1.E+04

1.E-01 1.E+00 1.E+01 1.E+02Frequency (1/s)

Vis

cosi

ty (

Pa.

s)

180°C

200°C

220°C

160

Fig. 4.6. Dynamic viscosity of polypropylene

1.0E+02

1.0E+03

1.0E+04

0.10 1.00 10.00 100.00

Frequency (1/s)

Com

plex

vis

cosi

ty (P

a.s)

210°C

220°C

230°C

161

a. Top view

b. Side view

Fig. 4.7. SEM of a micro-channel.

162

Fig. 4.8. Measured filling lengths in microchannels for PMMA in the long mold.

0

50

100

150

200

250

300

0.001 0.01 0.1 1 10

Main Flow Velocity (m/s)

Cha

nnel

Hei

ght (

Mic

orm

eter

)

80°C; HP=500 PSI

80°C; HP=0 PSI

163

Fig. 4.9. Measured filling lengths in microchannels for PP in the long mold.

0

100

200

300

400

500

600

0.001 0.01 0.1 1 10

Main Flow Velocity (m/s)

Cha

nnel

Hei

ght

(Mic

orm

eter

)

80°C; HP=500 PSI

80°C; HP=0 PSI

25°C; HP=0 PSI

164

Fig. 4.10. Measured filling lengths in microchannels for PMMA in the long mold.

0

5

10

15

20

25

30

35

40

45

50

0.01 0.1 1 10Main flow velocity (m/s)

Fill

ing

leng

th (

µ

m)

80°C; HP=500 PSI

80°C; HP=0 PSI

165

Fig. 4.11. Measured filling lengths in microchannels for PP in the long mold.

0

50

100

150

200

250

300

0.001 0.01 0.1 1 10Main flow velocity (m/s)

Fill

ing

leng

th (

µ

m)

80°C; HP=0 PSI

25°C; HP=0 PSI

166

Fig. 4.12. Measured filling lengths in microchannels for PP in the short mold.

0

100

200

300

400

500

600

700

0.001 0.01 0.1 1 10

Main Flow Velocity (m/s)

Cha

nne

l Hei

ght

(Mic

orm

eter

)

Short Mold, Channel A

Short Mold, Channel B

Long Mold, Channel B

167

Fig. 4.13. The cavity pressure profile in the long mold and the short mold.

168

Fig. 4.14. The filling length vs. Fourier number.

0

0.2

0.4

0.6

0.8

1

1.2

0.01 0.1 1 10 100 1000Fo

Fill

ing

leng

th /

Dep

th

100 microns, Short B

100 microns, Short A

100 microns, Long A, B

169

Fig. 4.15 The effect of packing stage on filling lengths.

(Melt temperature 240°C, mold temperature 25°C, main flow velocity 0.2 m/s)

0

10

20

30

40

50

60

70

80

0 4 8 12 16 20 24

Cav

ity

pres

sure

(M

Pa)

Start of packing

0

50

100

150

200

250

300

350

400

25.40 27.94 30.48 30.73 30.99 34.29 50.80

Shot size (mm)

Fill

ing

leng

th (µ

m)

201 mm/s

Start of packing

25.40 27.94 30.48 30.73 30.99 34.29 50.800

10

20

30

40

50

60

70

80

0 4 8 12 16 20 24

Cav

ity

pres

sure

(M

Pa)

Start of packing

0

50

100

150

200

250

300

350

400

25.40 27.94 30.48 30.73 30.99 34.29 50.80

Shot size (mm)

Fill

ing

leng

th (µ

m)

201 mm/s

Start of packing

25.40 27.94 30.48 30.73 30.99 34.29 50.80

170

Fig. 4.16 The effect of holding pressure on filling lengths.

(Melt temperature 240°C, mold temperature 25°C, main flow velocity 0.2 m/s)

0

50

100

150

200

250

300

350

400

450

0 500 1000 1500 1900

Hold pressure (psi)

Fill

ing

leng

th (µ

m)

Main flow velocity 201 mm/s

171

Fig. 4.17. Comparison of the filling lengths between the simulation and experiment with

constant heat transfer coefficients. Main flow heat transfer coefficient=25000 W/m2.K.

0

100

200

300

400

500

600

1 10 100 1000 10000

Main flow velocity (mm/s)

Fill

ing

leng

th (

mic

ron)

Expr.

h=500

h=2000

h=2500

172

Fig. 4.18. Comparison of the filling lengths between the simulation and experiment with constant heat transfer coefficients. Main flow heat transfer coefficient=2000 W/m2.K.

0

100

200

300

400

500

600

1 10 100 1000 10000

Main flow velocity

Fill

ing

leng

th (

mic

ron)

Expr.

h=500

h=2000

h=25000

173

Fig. 4.19. Comparison of the filling lengths between the simulation and experiment with

variable heat transfer coefficient.

0

100

200

300

400

500

600

1 10 100 1000 10000

Main flow velocity (mm/s)

Fill

ing

len

gth

(m

icro

n)

Expr. Tm=25CSimu. Tm=25C

Expr. Tm=80CSimu. Tm=80C

174

Fig. 4.20. Schematic of the mold with thickness of 1 mm.

50.8

mm

152.4 mm76.2 mm

P transducer P transducer P transducer

50.8

mm

152.4 mm76.2 mm

P transducer P transducer P transducer

175

Fig. 4.21. Heat capacity of HDPE and PS.

0

2000

4000

6000

8000

10000

12000

0 50 100 150 200 250 300 350

T (oC)

Cp

(J/k

g.o C

)

PS

HDPE

176

Fig. 4.22. Specific volume of HDPE.

0.9

1.0

1.1

1.2

1.3

1.4

1.5

273 323 373 423 473 523

Temperature (K)

Spec

ific

vol

ume

(cm3 /g

)

0 MPa

50 MPa

100 MPa

150 MPa

177

Fig. 4.23. Specific volume of PS.

0.90

0.95

1.00

1.05

1.10

273 323 373 423 473 523

Temperature (K)

Spec

ific

vol

ume

(cm3 /g

)

0 MPa

50 MPa

100 MPa

150 MPa

178

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04

Shear Rate/Frequency (1/s)

Vis

cosi

ty (

Pa.

s)

180°C

200°C

220°C

180C Fit

200C Fit

220C Fit

Fig. 4.24. Experimental and fit viscosity vs. shear rate/ frequency for PS.

179

1.E+01

1.E+02

1.E+03

1.E+04

1.E+05

1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04

Shear Rate/Frequency (1/s)

Vis

cosi

ty (

Pa.

s)

160°C180°C200°C160°C Fit180°C Fit200°C Fit

Fig. 4.25. Experimental and fit viscosity vs. shear rate/ frequency for HDPE.

180

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8

Time (s)

Cav

ity

Pre

ssur

e (M

Pa)

Effect of pressure not consideredPressure-dependent v

Fig. 4.26. Comparison of cavity pressure with/without the effect of pressure on

specific volume.

181

0

10

20

30

40

50

60

70

80

0 1 2 3 4 5 6 7

Time (s)

Cav

ity

Pre

ssur

e (M

Pa)

Effect of pressure not consideredPressure-dependent viscosity

Fig. 4.27. Comparison of cavity pressure with/without the effect of pressure on

viscosity.

182

0

10

20

30

40

50

60

70

80

0 2 4 6 8

Time (s)

Cav

ity

Pre

ssur

e (M

Pa)

h=25000h=1500

Fig. 4.28. Comparison of cavity pressure with different heat transfer coefficients.

183

0

10

20

30

40

50

60

70

80

0 2 4 6 8

Time (s)

Cav

ity

Pre

ssur

e (M

Pa)

Constant CpTemperature-dependent Cp

Fig. 4.29. Comparison of cavity pressure with constant Cp and temperature-

dependent Cp.

184

0

10

20

30

40

50

60

70

80

0 2 4 6 8

Time (s)

Cav

ity

Pre

ssur

e (M

Pa)

No juncture lossJuncture loss included

Fig. 4.30. Comparison of cavity pressure with/without juncture loss.

185

Fig. 4.31. Pressure profiles right after the gate and at the end of the cavity at the

injection speed of 76.2 mm/s and the melt temperature of 230 and 250°C.

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10 12 14 16 18Time (s)

Pre

ssu

re (

MPa

)

Pressure after Gate, 250°CPressure at End, 250°CPressure after Gate (230°C)Pressure at End (230°C)

186

Fig. 4.32. Pressure profiles right after the gate at the melt temperature of 230°C with

different injection speeds.

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10 12 14

Time (s)

Pre

ssur

e (M

Pa)

12.7 mm/s76.2 mm/s508 mm/s

187

Fig. 4.33. Pressure profiles at the end of the cavity at the melt temperature of 230°C

with different injection speeds.

0

5

10

15

20

25

30

35

40

0 2 4 6 8 10 12 14

Time (s)

Pre

ssur

e (M

Pa)

12.7 mm/s76.2 mm/s508 mm/s

188

Fig. 4.34. Comparison of experimental and predicted pressure drop at the injection

speed of 12.7 mm/s.

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8Time (s)

Cav

ity

Pre

ssu

re (

MP

a)

Experimental pressureEffect of pressure on v not consideredP-independent viscosityPressure-dependent viscosityh=1500

189

Fig. 4.35. Comparison of experimental and predicted pressure drop at the injection

speed of 508 mm/s.

0

10

20

30

40

50

60

70

80

90

0 2 4 6 8 10 12 14Time (s)

Cav

ity

Pre

ssur

e (M

Pa)

Experimental pressure

Effect of P on v not considered

P-independent viscosity

P-dependent viscosity

h=1500

190

CHAPTER 5

CHARACTERIZATION OF VIRGIN/POST-CONSUMER BLENDED

HIGH IMPACT POLYSTYRENE RESINS FOR INJECTION MOLDING

5.1 INTRODUCTION

Plastics have become a common materials choice in many new products and

millions of kilograms of plastics are used annually [Society of the Plastics Industry,

2001]. The attention paid to polymer recycling has increased in the past decade because

more efficient re-use of materials will reduce the quantities of plastics sent to landfills as

well as reduce raw material extraction. Furthermore, the advent of “take-back”

legislation accelerates waste prevention practices [Gamalski, 1996; Meffert and

Kirchgeorg, 1997; Hubschman, et al., 1995]. However, only a small amount of plastics

is reused as introduced in Section 2.1. Reducing virgin resin consumption can be

achieved by reduction of material requirement or resin recycling. One strategy is to use

thinner wall molding to reduce the quantity of material required. However, thin-wall

molding requires high injection speed, high injection pressure with polymers that could

191

withstand high shear rates and possible molecular degradation. Another strategy is to

recycle resin. In this study, we focus on resin cycling. However, how to characterize the

post-consumer resin (PCR) and how to increase the percentage of the post-consumer

resin are two of the problems in recycling plastic.

Currently, only less than one percent of HIPS is recovered from the total 19%

market share [Dillon and Aqua, 2000]. Two big challenges to reuse post-consumer resin

are material contamination and degradation. Post-consumer polymers may be

contaminated from other materials [Langerak, 1997]; post-consumer products may

contain polymer blends as well as additives such as reinforcements, paint, or flame

retardants [Dillon, 1999]. Another challenge is the material degradation because

returned polymers have been exposed to various thermal and mechanical conditions.

Thus, molders are reluctant to use recycled plastics because extensive experimental

testing is required to identify plausible use and determine molding parameters.

Recyclers currently select between options such as incineration or downcycling.

The major problem to reuse PCR is that polymer databases do not contain

information about PCR. Beside the material selection assistance, polymer databases are

used in mold filling simulation to design, reduce experimental time to decide processing

parameters, and predict possible problems. If molders must use trial and error to

determine PCR molding parameters, then a higher setup time is required for PCR than

for a virgin resin that is included in the database. Manufacturers usually use virgin resin

192

databases to decide processing parameters to reduce time because molders cannot easily

decide them without the material characterization of PCR.

Therefore, our initial investigation began with characterization of the post-

consumer resin. The viscosity is one of the basic properties for the reuse of the post-

consumer resin. The melt viscosity of the post-consumer resin was measured and the

virgin resins were identified with the same melt viscosity as the PCR. Next, the melt

viscosities of post-consumer and virgin resin blends were measured. Then the

mechanical properties of blends were measured and the effect of different virgin resins

and weight percentage of virgin resins were discussed. This investigation helped us

evaluate the viability of reusing the PCR in new injection molded products. Our goal is

to characterize the relationship between the ratio of recycled content to virgin content

and the mechanical properties. The mechanical properties, including tensile properties,

flexural properties, and impact properties, of the blends with different percentages of

reuse resin were analyzed through experiments. Furthermore, we investigated the

molecular weight and morphology of molded parts to help explain and predict the

properties of recycled blends for injection molding. Understanding the relationship

between rheological and design characteristics will provide both suppliers (recyclers)

and customers (molders) with valuable insights regarding viable uses for post-consumer

resins. Meanwhile, we introduce a sequence of steps to obtain PCR input for mold

filling simulation. The purpose is to reduce the amount of experimental time to

determine molding parameters. The method is tested by molding ASTM specimens and

a thin-wall application in film canisters.

193

5.2 EXPERIMENTAL

5.2.1 Characterization of Material

It is important to identify the post-consumer polymer properties. In general, it is

nearly impossible to identify the original resin manufacturer for post-consumer polymers

in electronics equipment. In our case, we only knew the polymer was labeled HIPS (high

impact polystyrene); we did not know the original resin manufacturer or product code.

Therefore, we tested the rheological properties of the PCR in order to identify the most

suitable "virgin resin” for the blends. The PCR material we used consisted of ground

pieces of printer and monitor housings.

The size of the fragments was greater than 100 mm. The incoming fragments

were inspected manually for metal contamination and then were shredded again to reduce

their size before mixing with virgin resins. The maximum dimension of the shredded

fragments was 1-10 mm, which was close to the size of the virgin resins.

The rheometer used was a Rheometrics Mechanical Spectrometer (RMS 800).

The rheological properties of the blends which consisted of different percentages of post-

consumer HIPS and virgin resins were also studied at three temperatures: 180ºC, 200ºC,

and 220ºC. Molded discs were used for the measurement of viscosity for the blends.

5.2.2 Measurement of Molecular Weight

The molecular weight was measured by GPC (Gel Permeation Chromotography).

The samples used were molded blends with 0%, 50%, and 100% Huntsman PS 702,

194

molded blends with 50% and 100% Nova PS 3350, and never molded, 100% virgin Nova

PS 3350. The solution was prepared by dissolving blends in THF (Tetrahydrofuran).

Each sample was analyzed twice with a running time of 45 minutes and an injection

volume of 200 µl. We report the average of the two runs in Table 5.1.

5.2.3 Microscopy and Spectroscopy

For the morphological measurement, the aim is to observe the dispersion of

rubber phase in polystyrene and the size of rubber domains because the rubber particles

can affect the mechanical properties. A Philip XL-30 FEG environmental scanning

electron microscope (ESEM) was used. The sample was stained by 1% OsO4 aqueous

solution for 15 days and carbon-coated for morphological measurements. The fracture

surfaces were observed with 15 KV power. The magnification in this study varied from

200x to 10,000x.

The purpose of the Raman spectroscopy tests is to determine if there is a

detectable difference in the absorption spectra for the PCR and the virgin high impact

polystyrene. The virgin resin Huntsman PS 702 was used in the experiment. The

infrared vibrational spectra were obtained using a Bruker Equinox 55 with IR Scope 1.

The instrument was operated in reflectance mode using the 15x microscope objective and

4 cm-1 resolution. OPUS software, version 2.2, was used for instrument control and data

handling.

The Raman vibrational spectra were obtained using a Chromex Raman 2000

spectrometer upon illumination by a 785 nm diode laser DSL and imaged on a

195

Photometrics 1024 X 256 pixel red enhanced CCD detector. The spectra were taken at a

180° collection angle with a depth of focus of several mm. The laser power was typically

50 mW with a spot size of 80 µm.

5.2.4 Processing Parameters for ASTM Specimens

To determine initial processing parameters, a mold filling simulation was run on

C-MOLD 97.7. C-MOLD is a set of integrated computer aided engineering (CAE)

simulations for plastics molding processes, including injection mold filling, post-filling,

cooling, part shrinkage and warpage. C-MOLD provides recommendations for

processing parameters such as fill time, inlet and melt temperature. CAE provides an

easy-to-use data visualizer for viewing mesh information and analysis results.

C-MOLD 97.7 was used to simulate filling our mold with one of the virgin resins,

Huntsman PS 702, which had the same viscosity versus shear rate as our PCR. The

ASTM mold consisted of six cavities, including two tensile bars, two sheets and two

discs. From the results of the mold simulation and several experimental trials, the

operating parameters, such as inlet melt temperature, melt temperature, and cooling time,

were selected to injection mold ASTM specimens.

The mold filling simulation required input for the resin properties. They can be

obtained from commercial resin databases or resin suppliers. However, resin databases

only contain virgin resin. So, we identified a virgin resin with similar viscosity to use as

input. In our approach, recyclers do not need to know the original resin manufacturers or

196

product codes. We assume that the PCR has been processed and sorted by manual

disassembly [Meacham, et al., 1999] or new bulk recycling methods [Arola and Biddle,

2000] so that it is not contaminated by other materials.

5.2.5 Physical Properties of ASTM Specimens

Six different weight percentages of blends were prepared, as shown in Table 5.2.

Two selected virgin resins, Huntsman PS 702 and Nova PS 3350, were used. These

virgin resins were selected because they had the close viscosity versus shear rate curve as

the PCR. The blends were mixed for one minute in a Little Ford Lodige Precision Mixer.

The ASTM specimens were prepared with a 50 ton Sumitomo injection molding

machine. The virgin material and post-consumer resin were mixed completely and then

were dried at 160ºF for 2 hours prior to injection molding. According to the results of the

mold design, the barrel temperature was set from 380ºF to 440ºF from the rear zone to

front zone. The mold temperature was kept at 77ºF.

For blends with Huntsman PS 702, the physical properties tested include: tensile

strength and modulus (ASTM D 638) at 23.3ºC and humidity 21%, flexural strength and

modulus (ASTM D 790) at 18.4ºC and humidity 12%, and notched Izod impact strength

(ASTM D 256) at 18.4ºC and humidity 21%. For blends with Nova PS 3350, all tests

were performed at 27.3ºC and humidity 30%.

Roughness and waviness measure the small-scale surface irregularities.

Roughness represents the range of groove heights of the surfaces while waviness is the

regression line (mean line) of the roughness profile. Two surface parameters, roughness

197

average (Ra) and waviness average (Wa) were measured. According to ISO, ANSI, and

DIN standards, Ra is the arithmetic average deviation of the roughness profile from the

roughness centerline, while Wa is the arithmetic average deviation of the waviness profile

from the waviness centerline [Sander, 1991]. The test was performed using the

Perthometer with a Gaussian filter type. The tests were conducted with a straight line

(entire trace) tilt correction and an evaluation range of 4.00 mm. One data point was

collected at each of five locations on each of three ASTM impact discs per blend for a

total of fifteen data points per blend.

5.2.6 Application

The ASTM test specimen mold is specially designed to minimize material

damage during molding. So, we tested the recycled material under high shear stress

condition to assess the ability of the material to withstand more realistic industrial use.

The film canister mold, loaned by Eastman Kodak Company, was used to test the post-

consumer/virgin polymer blends and is a thin-wall application compared to the original

printer and monitor housings. The film canister is shown in Fig. 5.1. The canister base

has variations in thickness as well as the recycling logo. In Table 5.3, the mold design

characteristics are listed.

C-MOLD 97.7 was used to simulate filling the film canister mold with the virgin

resin, Huntsman 702. From the results of simulation, combined with experimental trials,

the operating parameters, such as inlet melt temperature, melt temperature, cooling time,

etc., were selected for making film canister specimens, as reported in section 5.3.6. At

198

the same operating parameters, six types of blends of different percentage of PCR were

used to mold canisters. In order to compare the two virgin resins, we processed blends

under the same conditions. However, Nova PS 3350 has a lower melt index of 0.27

g/min compared to the Huntsman PS 702 melt index of 0.75 g/min [IDES, 1999]. Thus,

we used a higher injection velocity for virgin Nova PS 3350 after several experimental

runs.

One of the quality indicators tested for the canisters was the tensile strength. The

specimens consisted of strips of uniform width and thickness. According to ASTM

standards, we chose 100 mm as the width with a thickness less than 0.8 mm. Since the

thickness of the canister wall was less than 1 mm, the ASTM D-882-97 was adjusted

slightly by shortening the length of the specimens from 101.6 to 98 mm and 46 mm. To

ensure uniform width, calipers with 0.25 mm capability were used to check the specimen

width. The utmost care was exercised in cutting specimens to prevent nicks and tears that

may cause premature failure. To eliminate the anisotropic effect of the material, two sets

of test specimens were prepared having their long axes parallel with and normal to the

flow direction. The flow direction of the material in injection molding was from the

bottom to top.

5.3 RESULTS AND DISCUSSION

5.3.1 Characterization of Material

The rheological properties of the ground post-consumer HIPS were studied at

three temperatures: 180°C, 200°C, and 220°C. Fig. 5.2 is the viscosity versus frequency

199

curve of the post-consumer material at 220°C. We identified two virgin resin candidates,

Huntsman PS 702 and Nova PS 3350, in the C-MOLD resin databases by comparing the

viscosity curves.

The viscosity of blends of different percentage of the recycled resins was also

investigated at three temperatures: 180ºC, 200ºC and 220ºC. Figs. 5.3 and 5.4 show the

viscosity of blends with Huntsman PS 702 or Nova PS 3350 versus frequency at

approximately 200ºC, respectively. It is found that all blends are shear thinning. It is also

shown that the viscosity increases with the increase of the percentage of the PCR.

5.3.2 Molecular Weight

The molecular weights are listed in Table 5.1. It is shown that molecular weight

and polydispersity of blends with Huntsman PS 702 increase with the increase of the

percentage of Huntsman PS 702. However, for blends with Nova PS 3350, the molecular

weight decreases with the increase of the percentage of Nova PS 3350, though the

polydisperisity increases as the percentage of Nova PS 3350 increases. We can see that

all blends, including recycled resin, have similar molecular weight and polydispersity,

which would lead us to predict similar mechanical properties.

5.3.3 Microscopy and Spectroscopy

Fig. 5.5 shows the environmental scanning electron microscope (ESEM) images

of different blends. It is found that for virgin resins, 100% Huntsman PS 702 and Nova

PS 3350, the outer surfaces are dotted with a broad range of rubber domain with many

200

large rubber particles. The diameter is about 2 µm. However, for 50% Huntsman PS 702

and 50% Nova PS 3350, we only observed relatively smaller rubber particles. The

diameter is about 1 µm. The surface structures for the 50% blends are less regular

compared to those of virgin resins. For the PCR, we did not observe well defined rubber

domains, and the surface was seemingly covered with poorly defined dispersed rubber-

phase and some very small particles which may be contaminants.

Figs. 5.6 and 5.7 show the Raman Spectroscopy and Infrared vibrational spectra

of recycled resin and virgin resin Huntsman PS 702, respectively. It is shown that

recycled resin and virgin resin consist of almost the same components. Combined with

the results of the molecular weight measurements, we predict that it is possible to mix the

recycled resin and virgin resin for potential synergistic improvement of their properties.

5.3.4 Processing Parameters for ASTM Specimens

At first, the geometry was evaluated and then the mesh for the C-COLD

simulation was created. Processing parameters for the ASTM specimens of Huntsman PS

702 from the C-MOLD simulation are given in Table 5.4.

To compare the mechanical properties of the blends of Huntsman PS 702 to the

properties of blends of Nova PS 3350, the same injection molding parameters were used

to prepare the specimens of blends of Nova PS 3350.

5.3.5 Physical Properties of ASTM Specimens

For the six blends of Huntsman PS 702, the minimum, maximum, and average for

the Ra and the Wa are shown in Figs. 5.8 and 5.9 respectively. As shown in the figures,

201

the roughness average was fairly stable for the various blends but the waviness average

was best for the 0% virgin material. Due to our sample size of fifteen data points per

blend, further tests are being conducted with a larger sample size.

For the blends of Huntsman PS 702, the results of the physical properties tested

are shown in Figs. 5.10-5.12. For each physical property, six samples were tested. The

data shown in Figs. 5.10-5.12 are the averages of each sample. Fig. 5.10 shows the

tensile modulus and tensile strength of the blends for two different virgin resins versus

weight percentage of virgin resin. It is found that generally, both the tensile strength and

tensile modulus decrease slightly with the increase of the weight percentage of virgin

resin for the blends with virgin resin Huntsman PS 702, while the tensile strength and

tensile modulus increase slightly with the increase of the weight percentage of virgin

resin for the blends with virgin resin Nova PS 3350. The standard deviation of 12

samples at each percentage was calculated for each physical property. The average of the

standard deviations for the six blends of the tensile strength and the tensile modulus are

0.63 and 67 respectively. Fig. 5.11 illustrates the results of flexural modulus and flexural

strength. It is shown that flexural strength, like the tensile strength for the blends of

Huntsman PS 702, decreases slightly. For the blends of Nova PS 3350, flexural strength

has the same trend as tensile strength and increases slightly. However, flexural modulus

has no specific changing trend for the blends of both Huntsman PS 702 and Nova PS

3350. The average of the standard deviations over the six blends of the flexural strength

and the flexural modulus are 0.60 and 46 respectively.

202

As shown in Fig. 5.12, the impact strength of the blends of Huntsman PS 702

increases with the increase of weight percentage of recycled HIPS when the percentage is

small. At 75% and greater recycled HIPS, the strength reaches a stable value. For impact

strength of the blends of Nova PS 3350, it decreases with the increase of weight

percentage of virgin resin when the percentage is small. At 75% and greater virgin resin,

the strength reaches a stable value. The average of the standard deviation over the six

blends of the impact strength is 2.6.

Though Raman Spectroscopy and Infrared vibrational spectra show that recycled

resin and virgin resin consist of almost the same components, and the blends have similar

molecular weight and polydispersity, ESEM shows that the different blends have very

different microstructure and different rubber domain sizes. Thus, it is not surprising that

the different blends have different mechanical properties because the mechanical

properties of HIPS can be affected by the amount of rubber added, the type of rubber,

rubber size distribution, phase volume, the degree of crosslinking, or the level of adhesion

[Hobbs, 1986; Cook, et al., 1993]. The reason for the higher tensile modulus, tensile

strength, flexural strength, and impact strength of PCR compared to Huntsman PS 702

probably results from the higher tensile modulus and tensile strength of the original

material or the addition of reinforcements in pure resin when the printers and monitors

were made. Also, the experiments demonstrated that the mechanical properties of

recycled HIPS were slightly lower than those of Nova PS 3350. It is interesting to note

that the mechanical properties of blends with Huntsman PS 702 and recycled resin are

slightly better than the properties of the selected virgin material Huntsman PS 702. Our

203

experiments demonstrate that it is possible to reuse the post-consumer resin. Relative to

the selected virgin materials with the same viscosities as the post-consumer resin, reuse of

the post-consumer resin is an attractive option.

We compared our 100% PCR tensile and flexural properties with those published

in a study comparing disassembled versus shredded HIPS from post-consumer television

sets [Langerak, 1997]. It is found that the tensile modulus of our blends is lower than that

of the disassembled or shredded HIPS in the published study [Langerak, 1997]; however

the tensile strength at yield of our blends is larger. It is also shown that the flexural

modulus of our blend is lower than that of disassembled or shredded HIPS in the other

study [Langerak, 1997], but the flexural strength is almost the same. The differences in

mechanical properties of the PCR in the two studies may result from the different brands

of the original materials.

5.3.6 Application

Before making the real film cans, the injection molding process was simulated by

C-MOLD 97.7. The mesh is shown in Fig. 5.13. The simulation results are listed in

Table 5.5.

Film canisters were made using post-consumer Huntsman HI/PS 702 virgin resin

blends. To obtain initial machine settings, we used the simulation results from C-MOLD

97.7 and IDES's handbook of injection molding specs [IDEAS, 1999]. The main

difference between these resources is the processing temperature. The handbook

recommended a lower temperature, 221°C, while C-MOLD recommended a higher

204

temperature, 243°C. After experimental trials, we selected the machine settings as shown

in Table 5.5.

The tensile tests for the film canisters were performed on the Instron machine.

The results are listed in Table 5.6. It is shown that the tensile strength of the blends with

Huntsman PS 702 increases with the increase of the weight percentage of recycled resin.

The reason is that Huntsman PS 702 has lower tensile strength than the PCR and thus the

PCR increases the tensile strength of the blend. If the PCR is cheaper and has a higher

tensile strength than a virgin resin with similar rheology, then the PCR can be selected to

increase the mechanical property or properties.

5.4 CONCLUSIONS

To determine the initial processing conditions for injection molding virgin/post-

consumer resin blends, a precharacterized resin must be designated for a C-MOLD

simulation. To select a precharacterized resin for the C-MOLD simulation, virgin resin

viscosity curves were matched with the PCR viscosity curve. Then the recommended C-

MOLD simulation processing parameters were further refined for the blends for the

ASTM test standard specimens by running several experimental runs. In our proposed

approach, we can characterize and represent the PCR in a mold filling simulation by the

virgin resin in the database. Experimental testing to determine injection molding

parameters for various blends is greatly reduced by this approach.

All blends have similar molecular weight and polydispersity. Furthermore, the

recycled resin and virgin resin consist of almost the same components, as shown in their

205

Raman and infrared spectra. For the ASTM specimens molded with either set of blends,

the mechanical properties are similar. The tensile modulus, tensile strength, and flexural

strength increase slightly with the increase of the weight percentage of PCR for the

blends of Huntsman PS 702. The impact strength increases with the increase of weight

percentage of PCR when the percentage is small and finally the strength reaches a stable

value. It is found that the physical properties of blends having recycled resin are better

than the properties of virgin resin Huntsman PS 702. On the other hand, the mechanical

properties of PCR with Nova PS 3350 are slightly lower when compared to the pure

virgin Nova PS 3350 resin.

206

Materials Mn Mw Polydispersity

100% Huntsman 702 58198 180875 3.06

50% Huntsman 702 56730 171486 3.03

0% Huntsman 702 55262 162099 2.93

100% Nova 3350 54129 196963 3.64

50% Nova 3350 55724 181306 3.26

Virgin Nova 3350 57577 183095 3.18

Table 5.1 Molecular weight (Number average Mn and weight average Mw)

and polydispersity

207

No Weight percentage Of virgin resin (%)

Weight percentage of Recycled material (%)

1 100 0

2 85 15

3 75 25

4 50 50

5 25 75

6 0 100

Table 5.2 Weight percentage blends

208

Description Film canister

Maximum dimension 49.40 mm

Maximum flow length 65 mm

Volume 560 mm 3

Thickness 0.76 mm

Gate geometry Rectangular,

0.130 in wide

0.075 in deep

Projected area 730 mm 2

Table 5.3 Mold design characteristics

209

Max machine clamp force 4.90E+007 N

Max machine injection volume 0.02 m3

Max machine injection pressure 1.8E+008 Pa

Max machine injection rate 0.006667 m3/s

Fill time 2.00 s

Post-fill time 12.08 s

Mold-open time 2 s

Ambient temperature 298 K

Min/max melt temperature 449.15/533.15 K

Transition temperature 365.15 K

Inlet melt temperature 522.09 K

Average coolant temperature 298 K

Table 5.4 Processing parameters from C-MOLD

210

Resin Huntsman HI/PS 702 Coolant Pure water The maximum flow length 65 mm Thickness 0.76 mm Projected area 7.3 cm 2 Volume 0.56 cm 3 Coolant channel diameter 7 mm Clamp force 50 ton(m) Mold open time 2 s Mold temperature 34.5°C Min. Processing temperature 176°C Max. Processing temperature 260°C Max. machine inj. Press. 180 MPa Melt temperature 242.9°C Fill time 0.49 s

Table 5.5 CMOLD parameters for film canister

211

wt% of virgin resin Tensile strength (MPa) of Hunstman PS 702

Tensile strength (MPa) of NOVA PS

3350 0% 17.54 17.54 25% 15.69 16.31 50% 16.02 16.36 75% 15.42 17.62 85% 14.76 17.91 100% 14.78 19.44

Table 5.6 Tensile strength of film canisters

212

Fig. 5.1. Film canister.

213

Fig. 5.2. Comparison of the viscosity curves for post-consumer HIPS

and virgin HIPS at 220°C.

1.E+02

1.E+03

1.E+04

1.E-02 1.E-01 1.E+00 1.E+01 1.E+02

Frequency (1/s)

Vis

cosi

ty (

Pa.

s)

PCR

Huntsman PS 702

Nova PS 3350

214

Fig. 5.3. Viscosity of Huntsman PS 702 blends with different percentages of post-

consumer resin at about 200°C.

1.E+02

1.E+03

1.E+04

1.E+05

1.E-02 1.E-01 1.E+00 1.E+01 1.E+02

Frequency (1/s)

Vis

cosi

ty (P

a.s)

0% at 198.0°C25% at 197.5°C

50% at 197.6°C75% at 197.5°C85% at 197.7°C

100% at 197.4°C

215

Fig. 5.4. Viscosity of Nova PS 3350 blends with different percentages of post-consumer

resin at about 200°C.

1.E+02

1.E+03

1.E+04

1.E+05

1.E-02 1.E-01 1.E+00 1.E+01 1.E+02

Frequency (1/s)

Vis

cosi

ty (P

a.s)

0% at 198.0 °C25% at 197.3 °C50% at 197.5 °C75% at 197.7 °C85% at 197.1 °C100% at 197.7 °C

216

Fig. 5.5. The images of different blends from ESEM

(The length of the scales in the figures are 2 µm).

(a) 100% Huntsman PS 702 (b) 100% Nova PS 702

(e) PCR

(c) 50% Huntsman PS 702 (d) 50% Nova PS 702

217

Fig. 5.6. Raman spectroscopy of injection-molded

post-consumer and Huntsman PS 702.

Huntsman PS

218

Fig. 5.7. Infrared vibrational spectra of injection-molded

post-consumer and Huntsman PS 702.

PC

Huntsman PS 702

219

Fig. 5.8. Average Ra for six blends of Huntsman PS 702.

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.00 0.25 0.50 0.75 0.85 1.00

Percentage of the virgin material

R(a

) [m

icro

met

ers]

220

Fig. 5.9. Average Wa for six blends of Huntsman PS 702.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0% 25% 50% 75% 85% 100%

Percentage of the virgin material

W(a

) [m

icro

met

ers]

221

Fig. 5.10. Tensile strength and tensile modulus vs. weight percentage of virgin resin.

0

5

10

15

20

25

30

0% 20% 40% 60% 80% 100%

Weight percentage of virgin resin

Tens

ile s

tren

gth

(MPa

)

0

500

1000

1500

2000

2500

Tens

ile m

udul

us(M

Pa)

Tensile strength of Huntsman PS 702

Tensile strength of Nova PS 3350

Tensile modulus of Huntsman PS 702

Tensile modulus of Nova PS 3350

222

Fig. 5.11. Flexural strength and flexural modulus vs. weight percentage of virgin resin.

0

5

10

15

20

25

30

35

40

45

50

0% 20% 40% 60% 80% 100%

Weight percentage of virgin resin

Flex

ural

str

engt

h (M

Pa)

0

500

1000

1500

2000

2500

Flex

ural

mod

ulus

(MPa

)

Flexural strength of Huntsman PS 702

Flexural strength of Nova PS 3350

Flexural modulus of Huntsman PS 702

Flexural modulus of Nova PS 3350

223

Fig. 5.12. Impact strength and tensile modulus vs. weight percentage of virgin resin.

0

20

40

60

80

100

120

0% 20% 40% 60% 80% 100%

Weight percentage of virgin resin

Impa

ct s

tren

gth

(MPa

)

Huntsman PS 702

Nova PS 3350

224

Fig. 5.13. Meshing model of the film canister.

225

CHAPTER 6

CONCLUSIONS AND RECOMMENDATIONS

6.1 FLOW MARKS

For alternate dull and glossy flow marks, the effect of polymer rheology,

injection speed, mold geometry, melt temperature, mold temperature, holding pressure,

injection pressure, and mold surface coatings on the appearance of the flow marks was

studied. It was found that the most important factor affecting the flow marks was

injection speed. The flow marks occurred above a critical wall shear stress, but

disappeared at high injection speeds. Mold geometry had an effect on the flow marks,

but mold temperature and melt temperature did not have much effect on the flow marks.

No difference was observed between the crystallinity of dull regions and shiny regions.

However, it was found from Scanning Electron Microscopy that the melt in dull regions

was only slightly oriented while the melt in shiny regions was highly oriented. It was

also found that coating these surfaces did not prevent the occurrence of the flow marks,

although it could alleviate them. It was also found that the polymer with the highest

dynamic viscosity, elastic modulus, first normal stress difference, transient extensional

viscosity, and longest relaxation time exhibited flow marks over a wide range of

processing conditions. Slip was not the cause of the generation of the alternate flow

marks. The generation of the flow marks was explained by an entry viscoelastic flow

instability.

226

Synchronous dull and glossy flow marks were also studied. The effect of

operating parameters, mold geometry, and mold surface coatings on the flow marks was

investigated. The flow marks occurred above a certain flow front velocity. It was also

found in the experiment that the flow marks were dimmer as the mold temperature was

increased. No difference was observed between the crystallinity of dull and shiny

regions. However, polymer was highly oriented in shiny region while it was slightly

oriented in dull regions. It was also found that mold surface coatings did not eliminate

the flow marks. Extrusion experiments showed that helical gross melt fracture occurred

for both HDPEs. Finally, it was proposed that an entry viscoelastic instability was the

reason for the generation of the synchronous flow marks.

For the future work, we will prove the mechanism of the entry flow instability.

More evidence is favored for the proposed mechanism. For example, the possible

pressure fluctuation relating to melt fracture (flow marks) will be monitored. Using the

glass window mold in our lab, the flow before the gate and the flow front will be

visualized and recorded by high-speed camcorder. Then the flow will be analyzed.

Moreover, the possibility of slip will be analyzed. The extensional viscosity will be

measured to describe the fountain flow more accurately, and its effect on the formation

of vortices will be analyzed. Furthermore, fundamental mechanism for the formation of

the flow marks will be studied. The detailed morphology, crystallinity and structure of

crystalloids, and the effective thickness of the flow marks will be investigated.

6.2 EXPERIMENTS WITH MICRO-FEATURES AND SIMULATION

ACCURACY IMPROVEMENT

Thin-wall injection molding with micro-features was studied experimentally and

numerically. The filling lengths in microchannels are affected by injection speed, mold

temperature and channel location. It was found that high injection speed or high mold

temperature results in longer filling length. Moreover, the filling lengths in

227

microchannels increase with the decrease in the filling time flowing from the

microchannels to the main flow end. Furthermore, the filling lengths in microchannels

are simulated by a hybrid simulation code with a combination of the momentum

equation and the Hele-Shaw model, and compared with experimental results. The code

has fewer elements and requires less computation time. The simulation shows that the

filling lengths in microchannels are sensitive to the heat transfer coefficients in the main

flow cavity and in the microchannel and extra attention is needed to determine proper

heat transfer coefficient. Using the variable heat transfer coefficient, the filling length in

the long mold is predicted accurately.

Our future work will study the thin-wall injection molding of smaller

microchannels with the width of 50 µm and the depth of 250 µm. The morphology of

the microchannels, demolding problem, filling, freezing pattern, repeatability, durability,

and the deformation of the wall of the microchannels will be studied. Moreover, the

filling lengths in microchannels with different main flow thicknesses will be compared

to study which main flow thickness is beneficial to long filling lengths. The argument is

that in the thick mold the melt temperature is high but the pressure drop is low; in the

thin mold the temperature is low but the pressure drop is high. So it is difficult to decide

which mold thickness is favorable to long filling lengths. Furthermore, the filling length

will be measured and it will be compared with simulation results. The effect of heat

transfer coefficients both in the main flow and in the microchannels will be paid full

attention.

For the cavity pressure, the simulation showed that the effect of pressure on the

specific volume is the most important factor to predict the peak cavity pressure. The

effect of pressure on the viscosity and the heat transfer coefficient are also significant.

The heat capacity and the juncture loss are relatively less important compared to other

factors considered here. Therefore, it is very important to use proper material property

228

models when running simulation of thin-wall injection molding. It was also shown that

the significant factors are somewhat different to predict maximum cavity pressure drop.

The effect of the pressure-dependent viscosity, the heat capacity, the heat transfer

coefficient, the juncture pressure loss and the pvT-data on the cavity pressure and

pressure drop were studied. Another important thermal property, thermal conductivity,

would be included for future work. Furthermore, future work could study the effect of

these properties on the filling length in main flow and even in microchannels.

When the injection speed was high, the discrepancy between the simulation

results and experimental data was large and no good agreement could be achieved no

matter what property models were used. So, the reason for the discrepancy might not be

included within the factors we considered. The possible reason may be the difference

between the set operating values and the actual conditions the machine reached. For

example, the actual injection speed is intrinsically slower than the speed one sets,

especially at high injection speeds, as the machine needs response time to reach the

desired constant injection speed. The actual temperature in the barrel may be different

from the set temperature. The effect of these differences should be checked.

Material property measurement and models will affect the simulation results and

proper conclusions. The pressure dependent viscosity was measured under relatively

low pressure and then extrapolated to high pressure. Future work should measure the

viscosity under very high pressure to get a more accurate pressure dependent viscosity

model. The heat capacity was measured at a low heating rate of 3.33ºC/s. It is very

useful to get the “true” value because the cooling rate is very fast in thin-wall injection

processes. The heat transfer coefficient has a large effect on the cavity pressure and the

default value 25,000 W/m2⋅K must be re-evaluated to obtain good simulation results

because other researchers’ work and the current work showed that the default is too

large.

229

Finally, the software itself may affect the final pressure prediction due to its

simplification, such as the assumption of Hele-Shaw flow. Hele-Shaw flow neglects

flow in the gapwise direction and gives the average information in the gapwise direction.

It cannot accurately predict the fluid behavior at the flow front and the flow near or at

solid walls, the phenomenon occurring at the merging of two or more streams (weld

lines), and the kinematics in ribs, gates, or sudden contractions/enlargement. Moldflow

is a 22

1D software and uses mid-plane mesh. So, developing the code with less

assumptions or 3-D mesh based on our group’s previous work may provide more

accurate pressure prediction.

6.3 REUSE OF HIPS

This part focuses on the mechanical and rheological properties of virgin and

recycled high impact polystyrene materials. The study shows that all blends have similar

molecular weight and polydispersity. Furthermore, the recycled resin and virgin resin

consist of almost the same components, as shown in their Raman and infrared spectra.

For the ASTM specimens molded with either set of blends, the mechanical properties are

similar. The tensile modulus, tensile strength, and flexural strength increase slightly

with the increase of the weight percentage of PCR for the blends of Huntsman PS 702.

The impact strength increases with the increase of weight percentage of PCR when the

percentage is small and finally the strength reaches a stable value. It is found that the

physical properties of blends having recycled resin are better than the properties of virgin

resin Huntsman PS 702. On the other hand, the mechanical properties of PCR with

Nova PS 3350 are slightly lower when compared to the pure virgin Nova PS 3350 resin.

Our experiments demonstrate that the PCR may have good material properties and may

even be used in a more challenging application.

230

Moreover, the study introduces a new approach to determine initial processing

parameters for injection molding of post-consumer resin. To determine the initial

processing conditions for injection molding virgin/post-consumer resin blends, we can

characterize and represent the PCR in a mold filling simulation by the virgin resin in the

database. This approach greatly reduces experimental testing to determine injection

molding parameters for various blends. This approach for plastics recycling is novel

because we started with an initial rheological investigation of PCR characteristics rather

than tracking the original virgin resin. We also tested our new approach by molding the

PCR in a thinner wall design application.

There are several areas of this research requiring more study in future. In our

study, two different virgin resins were identified by PCR characterization. Both

candidates had similar viscosity versus shear rate curves, but different melt flow indices.

Because plastics have complex properties, further study is needed to identify the

properties of the unknown PCR, and then find virgin resins that match additional

characteristics, such as mechanical properties. Then, the mechanical properties of a

specific design with different percentage of PCR will be predicted. It will further

improve the decision tool to decide the threshold of recycling.

Our study used HIPS from computer and monitor housing. More cases are

needed to get more general conclusions. To investigate the sensitivity of our approach to

grade mixtures is an interesting extension of this work. Because shredding different

plastic parts may generate a reground mixture of HIPS PCR grades, it will be useful to

determine whether the viscosity versus shear rates of the resin grade mixture could be

used to identify a proxy virgin resin.

231

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