UNIVERSITI TEKNIKAL MALAYSIA MELAKA

A STUDY TO DETERMINE THE BEST COMBINATION OF

FDM PROCESS PARAMETERS USING TAGUCHI METHOD TO

OPTIMIZE THE BUILD TIME AND SURFACE QUALITY

This report submitted in accordance with requirement of the Universiti Teknikal

Malaysia Melaka (UTeM) for the Bachelor Degree of Manufacturing Engineering

(Manufacturing Design) (Hons.)

by

NG MEE CHIN

B051210015

921222-07-5478

FACULTY OF MANUFACTURING ENGINEERING

2016

UNIVERSITI TEKNIKAL MALAYSIA MELAKA

BORANG PENGESAHAN STATUS LAPORAN PROJEK SARJANA MUDA

TAJUK: A Study To Determine The Best Combination Of FDM Process Parameters

Using Taguchi Method To Optimize Build Time And Surface Quality

SESI PENGAJIAN: 2015/16 Semester 2

Saya NG MEE CHIN

mengaku membenarkan Laporan PSM ini disimpan di Perpustakaan Universiti Teknikal Malaysia Melaka (UTeM) dengan syarat-syarat kegunaan seperti berikut:

1. Laporan PSM adalah hak milik Universiti Teknikal Malaysia Melaka dan penulis.2. Perpustakaan Universiti Teknikal Malaysia Melaka dibenarkan membuat salinan

untuk tujuan pengajian sahaja dengan izin penulis.3. Perpustakaan dibenarkan membuat salinan laporan PSM ini sebagai bahan

pertukaran antara institusi pengajian tinggi.

4. **Sila tandakan (√)

SULIT

√ TERHAD

TIDAK TERHAD

(Mengandungi maklumat yang berdarjah keselamatan atau kepentingan Malaysia sebagaimana yang

Termaktub dalam AKTA RAHSIA RASMI 1972)

(Mengandungi maklumat TERHAD yang telah ditentukan

oleh organisasi/badan di mana penyelidikan dijalankan)

Alamat Tetap:

8-7-13, Persiaran Paya Terubong

Satu, Ralau, 11900 Bayan Lepas

Pulau Pinang.

Tarikh: _________________________

Disahkan oleh:

Cop Rasmi:

Tarikh: _______________________

** Jika Laporan PSM ini SULIT atau TERHAD, sila lampirkan surat daripada pihak berkuasa/organisasi berkenaan dengan menyatakan sekali sebab dan tempoh laporan PSM ini perlu dikelaskan sebagai SULIT atau TERHAD.

DECLARATION

I hereby, declared this report entitled “A Study To Determine The Best

Combination Of FDM Process Parameters Using Taguchi Method To Optimize

The Build Time And Surface Quality” is the results of my own research except as

cited in references.

Signature : ………………………………………….

Author’s Name : NG MEE CHIN

Date : 25 JUNE 2016

APPROVAL

This report is submitted to the Faculty of Manufacturing Engineering of UTeM as

a partial fulfillment of the requirements for the degree of Bachelor of

Manufacturing Engineering (Manufacturing Design) (Hons.). The member of the

supervisory is as follow:

………………………………

(DR. SHAJAHAN BIN MAIDIN)

i

ABSTRAK

Kaedah Taguchi adalah alat yang berkesan diperkenalkan untuk pengoptimuman

produk atau proses kualiti. Produk yang dihasilkan oleh ABS Fused Deposition

Model (FDM) mempunyai hasil yang tersendiri yang berbeza dengan perubahan

parameter proses mesin seperti orientasi membina, ketebalan lapisan dan sudut raster.

Prestasi bahagian yang dihasilkan melalui Stratasys FDM 400 mesin MC

diperhatikan masa membina dan diukur untuk kekasaran permukaan. Dalam usaha

untuk mencapai prestasi optimum bahagian yang dihasilkan, Kaedah Taguchi telah

dilaksanakan. Dalam projek ini, pelbagai ortogon daripada L9 (33) telah digunakan

dan 9 keping sampel telah dibina untuk 3 parameter iaitu: membina orientasi,

ketebalan lapisan dan sudut raster dengan 3 tahap setiap parameter. Sampel itu direka

menggunakan SolidWorks dan dibina menggunakan Stratasys FDM 400 mesin MC.

Sampel diperhatikan masa membina dan kemudian diuji untuk kekasaran permukaan

menggunakan Mitutoyo Surftest SJ 301. Keputusan telah diperolehi dan data

dianalisis. Data menunjukkan bahawa sampel dengan kombinasi parameter XY

orientasi, ketebalan lapisan 0.03302 cm dan sudut raster 900 mencapai masa

membina yang paling singkat manakala data yang menunjukkan bahawa sampel

dengan kombinasi parameter XY orientasi, ketebalan lapisan 0.01778 cm dan raster

sudut 300 mencapai kekasaran permukaan purata yang paling rendah mengikuti nilai

Ra masing-masing. Oleh itu, keputusan ini menunjukkan bahawa ciri-ciri produk

yang dihasilkan menggunakan Stratasys FDM 400 MC berbeza dengan kombinasi

yang berbeza parameter proses dan Kaedah Taguchi menyediakan penyelesaian

untuk menentukan kombinasi yang optimum dengan jumlah minimum eksperimen.

ii

ABSTRACT

Taguchi Method is an effective tool introduced for the optimization of a product or

process quality. The ABS product produced by Fused Deposition Modeling (FDM)

has its own unique result which varies with the changes of the process parameters of

the machine such as build orientation, layer thickness and raster angles. The

performance of the part produced via Stratasys FDM 400 MC machines was

observed for build time and measured for surface roughness. In order to achieve the

optimum performance of the produced part, the Taguchi Method was employed. In

this project, an orthogonal array of L9 (33) was used and 9 pieces of samples were

determined for 3 parameters namely: build orientation, layer thickness and raster

angles with 3 levels each. The sample was designed using SolidWorks and fabricated

using Stratasys FDM 400 MC machines. The samples were observed for build time

and then tested for surface roughness using Mitutoyo Surftest SJ 301. The results

were obtained and data was analysed. The data shows that the samples with

parameters combination of XY orientation, layer thickness of 0.03302 cm and raster

angle of 900 achieved the shortest build time while the data shows that the samples

with parameters combination of XY orientation, layer thickness of 0.01778cm and

raster angle of 300 achieved the lowest average surface roughness, Ra value

respectively. Hence, this results show that the properties of the product produced

using Stratasys FDM 400 MC vary with the different combination of process

parameters and the Taguchi Method provides the solution of determining the

optimum combination with minimum number of experiment.

iii

DEDICATION

I would like to dedicate this work to my

Beloved parents

Dearest siblings

Honorable supervisor and lecturers

Supportive friends and mates

iv

ACKNOWLEDGEMENT

I would like to express my gratitude to my supervisor, Dr. Shajahan bin Maidin for

the continuous encouragement, invaluable supervision, timely suggestions and

inspired guidance in bringing the Final Year Project to a successful completion.

In addition, I would like to express my gratitude to technicians for permitting me to

make use of the facilities available in the laboratory to carry out the project

successfully. Last but not least, I express my sincere thanks to all my friends and

parents who have patiently extended all sorts of help for accomplishing the Final

Year Project.

v

TABLE OF CONTENT

Abstrak i

Abstract ii

Dedication iii

Acknowledgement iv

Table of Contents v

List of Tables ix

List of Figures x

List Abbreviations, Symbols and Nomenclatures xiii

CHAPTER 1: INTRODUCTION 1

1.1 Introduction 1

1.2 Problem Statement 2

1.3 Objective 3

1.4 Scope 4

CHAPTER 2: LITERATURE REVIEW 5

2.1 Additive Manufacturing (AM) 5

2.2 Eight Generic AM Processes 6

vi

2.3 Molten Material Systems 8

2.3.1 Fused Deposition Modeling (FDM) 9

2.3.2 FDM Process 9

2.3.3 FDM Materials 10

2.3.4 Application of FDM 14

2.3.5 Advantages of FDM 14

2.3.6 Disadvantages of FDM 15

2.4 Application of AM 16

2.5 Advantages of AM 19

2.6 Disadvantages of AM 20

2.7 Taguchi Method Background 21

2.7.1 Selection of Design or Process Parameters 22

2.7.2 Design of Experiment 23

2.7.3 Orthogonal Arrays 28

2.7.4 Analysis of Variance 29

2.7.5 Signal to Noise Ratio 31

2.8 FDM Parameter Optimization 36

2.8.1 Surface Roughness 36

2.8.2 Build Time 37

2.8.3 Build Orientation 38

2.8.4 Stair-case effect 40

2.8.5 Dimensional Accuracy 41

vii

2.8.6 Layer Thickness 41

2.8.7 Part Deposition 42

CHAPTER 3: METHODOLOGY 43

3.1 Introduction 43

3.2 Flow Chart 44

3.3 Project Implementation Procedure 47

3.3.1 Phase 0: Planning 47

3.3.2 Phase 1: Detail Design 48

3.3.3 Phase 2: Preparation of Specimen 50

3.3.4 Standard Operating Procedure 51

3.3.4.1 Stratasys FDM 400 MC machines 51

3.3.4.2 Fabrication of Mounting Brackets 55

3.3.4.3 Mitutoyo Surftest SJ-301 56

3.3.4.4 Meiji Stereo Microscope 58

3.3.5 Phase 3: Collection of Data 59

3.3.6 Phase 4: Result and Analysis 59

3.3.7 Phase 5: Conclusion and Recommendation 60

CHAPTER 4: RESULT AND DISCUSSION 61

4.1 Introduction 61

4.2 Parameter Combination 62

viii

4.3 Build Time 63

4.3.1 Analysis of data 63

4.3.2 ANOVA Analysis 67

4.4 Surface Roughness 71

4.4.1 Analysis of data 71

4.4.2 Macroscopic Inspection 79

4.4.3 ANOVA Analysis 81

4.5 Sustainability Development 85

CHAPTER 5: CONCLUSION AND RECOMMENDATION 87

5.1 Conclusion 87

5.2 Recommendation 89

REFERENCES 91

APPENDIX A Gantt Chart for Project 1 102

APPENDIX B Gantt Chart for Project 2 105

ix

LIST OF TABLES

2.1 Basic FDM material and their characteristics 11

2.2 L-4 (23) Orthogonal Array 28

3.1 List of parameters with its values in each level 51

3.2 The Orthogonal Array L9 (33) derived using Taguchi method 55

4.1 Different combination of parameter settings for each experimental run 62

4.2 Build Time Result for mounting brackets 63

4.3 Percentage contributions of parameters on build time 68

4.4 P-value analysis 70

4.5 Surface Roughness Result for 9 mounting brackets produced 72

4.6 Percentage contributions of parameters on surface roughness 82

4.7 P-value analysis 84

x

LIST OF FIGURES

2.1 Eight Generic AM Processes 6

2.2 FDM Process 9

2.3 AM application timeline 17

2.4 Prosthetic Jaw 18

2.5 Taguchi Loss of Function 22

2.6 Nine steps used to investigate a process and optimize the performance of the

process 24

2.7 Experimental Design using Orthogonal Array 27

2.8 Smaller is Better Approach 32

2.9 Larger is Better Approach 33

2.10 Nominal is Better Approach 34

2.11 Stair stepping effect 40

3.1 Flow of the Project 44

3.2 Isometric View of Mounting Bracket in XY direction 48

3.3 Isometric View of Mounting Bracket in XZ direction 49

3.4 Isometric View of Mounting Bracket in YZ direction 49

3.5 Detail design of Mounting Bracket with dimensions 50

3.6 Stratasys FDM 400 MC machines 52

xi

3.7 Ultrasonic Tank 54

3.8 Mounting Brackets Produced using Stratasys FDM 400 MC machines 55

3.9 Average Surface Roughness, Ra value taken using Mitutoyo

Surftest SJ-301 56

3.10 Touch Probe is used to measure the Average Surface Roughness, Ra

value using Mitutoyo Suftest SJ-301 57

3.11 Meiji Stereo Microscope 58

4.1 Build time for each experimental run 65

4.2 Percentage contributions of parameters on build time 68

4.3 Pareto Chart on build time 69

4.4 Average Surface Roughness, Ra value for each experimental run 75

4.5 Voids effect on different layer thickness 76

4.6 Stair case effect 77

4.7 Voids present in a specimen with raster angle of 600 78

4.8 Experimental run 1 is the combination of XY orientation,

layer thickness of 0.01778 cm and raster angle of 300 gives the

lowest surface roughness which indicates the best surface quality 79

4.9 Experimental run 9 with the combination of YZ orientation,

layer thickness of 0.03302cm and raster angle of 450 gives the

highest surface roughness which indicates bad surface quality 80

4.10 Percentage contributions of parameters on surface roughness 82

xii

4.11 Pareto Chart on surface roughness 83

xiii

LIST OF ABBREVIATIONS, SYMBOLS AND

NOMENCLATURE

ABS - Acrylonitrile butadiene styrene

Adj MS - Adjusted Mean Square

Adj SS - Adjacent Sum of Squares

AM - Additive manufacturing

AMC - Advanced Manufacturing Center

ANOVA - Analysis of Variance

BASS - Break Away Support System

BS - British Standard

CAD - Computer-aided Design

CAM - Computer-aided Manufacturing

CNC - Computer Numerical Control

DOE - Design of Experiment

EtO - Ethylene oxide

FDM - Fused Deposition Modeling

FKP - Fakulti Kejuruteraan Pembuatan

GA - Genetic Algorithm

ISO - International Standard Organisation

OA - Orthogonal Array

PC - Polycarbonate

xiv

PC-ABS - Polycarbonate-Acrylonitrile butadiene styrene

PC-ISO - Polycarbonate ISO

PPSF - Polyphenylsulfone

Ra - Roughness Average

S/N - Signal to Noise

SOP - Standard Operating Procedure

STL - Stereolithography

ULTEM 9085 - Polyetherimide

US - Unites States

UTeM - Universiti Teknikal Malaysia Melaka

3D - 3 Dimension

1

CHAPTER 1

INTRODUCTION

This chapter introduces the project and briefly describes about the objectives and the

scope of the study. This chapter will give an overview on the implementation of the

project.

1.1 Introduction

Resit and Edwin (1991) proposed that Taguchi Method is a popular method used to

provide systematic and efficient methodology for design optimization. Therefore, an

efficient way to enhance competitiveness in improving the quality of products is to

conduct Taguchi Methods to make products and processes robust during early product

design and development stage. Taguchi method focuses on four business objectives in

market which are short development time, low cost, high performance and high quality.

On the other hand, Omar et al. (2015) presented that fused deposition modeling is an

additive manufacturing technology which can construct physical models from computer-

2

aided design (CAD) software automatically by using layers deposition of extrusion

materials. In fact, fused deposition modeling is one of the additive prototyping processes

which can generate a prototype from plastic material by laying track of semi molten

plastic filament on to a platform in a layer wise manner from the top to bottom. The

layer generation result from solidification is because of heat conduction. In fact,

reduction of product development cycle time is a major consideration in industries to

remain competitive in the market place. Therefore, traditional product development

technology has been changed to rapid fabrication techniques, for instance, additive

prototyping processes.

The main purpose of the project is to determine how the best combination of the

parameters which are the layer thickness, raster angle and build orientation influence the

build time and surface roughness of Fused Deposition Modeling produced test specimen.

Experiments will be conducted using Taguchi’s design of experiments with three levels

for each factor. The combined set of different parameters can be produced using

Orthogonal Arrays. Furthermore, the project studies the significance parameters that

affect the build time and surface roughness of the FDM process using Analysis of

Variance respectively.

1.2 Problem Statement

Ranjit (2001) pointed out that the build time of a certain additive manufactured part or

product is concerned by industry due to it affects the lead time of the product. The

shorter the build time of the product, the better is the benefit to the company. Bharath et

al. (2000) discussed that surface quality plays a very important role in manufacturing

precise parts, for instance, aerospace components and parts with critical dimensions.

This is because product with good surface finish can ensure dimensional accuracy and

3

eliminate cost for post-processing processes to obtain desired surface quality. In

addition, Royal Academy of Engineering (2013) proposed that AM technology is not as

competitive as a conventional method such as injection moulding, casting and CNC

machining. In fact, build orientation, layer thickness and raster angle are those process

parameters that will influence the build time and surface roughness. The combinations of

the different settings of the parameters will produce parts with different build time and

surface roughness. Design of experiment using Taguchi methods to determine best

combinations and the number of runs of the experiment will be carried out. The best

combinations of the different settings of the parameters for build time and surface

roughness are then identified.

1.3 Objective

The objective of this study is as follows:

i. To optimize the fused deposition modeling process parameters by using

Taguchi’s method.

ii. To produce CAD model of FDM test specimen and build them on a FDM

machine using ABS material.

iii. To determine combinations of the different settings of the FDM parameters in

which it can produce the shortest build time and best surface quality.

iv. To determine the optimum parameters which will influence the build time and

surface roughness.

4

1.4 Scope

This project covers the study of how the combination of different parameters such as

build orientations, layer thickness and raster angle affects the build time and surface

roughness of the mounting bracket produced using FDM process. The mounting bracket

is drawn using Solidwork 2012 and converted to STL files to be readable by FDM

machine. Then, the FDM process will be carried out at FKP Ground Floor, Block B,

AMC laboratory using Stratasys FDM 400 MC. The material used in the FDM process is

ABS-M30i thermoplastic materials. Then, the mounting brackets produced are measured

for surface roughness using Mitutoyo Surftest SJ-301 in FKP Ground Floor, Block B,

Metrology Laboratory. Each area of the mounting bracket is repeated three times to

obtain much more precise average surface roughness Ra value. In addition, macroscopic

inspection will be carried out to examine the surface quality of the part produced. Two

mounting brackets produced which have the best and the worst surface quality are

examined under Meiji Stereo Microscope located in FKP Ground Floor Block B,

Metrology Laboratory to see their difference in structure. The process parameters are

optimized using Taguchi Method. By applying Taguchi in the experiment, we can

determine the best combinations of process parameters in which the combination has the

shortest build time and the best surface finish.

5

CHAPTER 2

LITERATURE REVIEW

This chapter discusses about the related knowledge of the project which cover the

introduction of the additive manufacturing, fused deposition modeling and Taguchi

Method.

2.1 Additive Manufacturing (AM)

Omar et al. (2015) have presented that additive manufacturing is one of the advanced

manufacturing technologies employed for making object layer upon layer directly from a

computer aided design (CAD) data file. Additive Manufacturing (AM) allows

customized design to be made. Hence, shape complexity is not an issue. We will

consume less time if we use AM to generate the part compared to conventional method.

Moreover, AM product will result in lower cost due to the absence of tooling needs.

FDM is one of the systems widely applied in additive manufacturing.

6

Furthermore, Pandey et al. (2006) have presented that AM is not similar compared to

lathing, milling and grinding as they will use material removal process to produce the

shape of the product.

2.2 Eight Generic AM Processes

Figure 2.1: Eight Generic AM Processes (Gibson et al., 2010)

From the Figure 2.1, it is clearly shown that there are eight steps needed to produce a

part for FDM machine.