FORGING PROCESS DESIGN FOR RISK REDUCTION
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate
School of The Ohio State University
By
Yongning Mao, M.S.
* * * * *
The Ohio State University
2009
Dissertation Committee: Approved by
Professor Rajiv Shivpuri, Adviser Professor Jose M. Castro __________________________
Professor Allen Yi Adviser
Industrial and Systems Engineering
Graduate Program
ii
ABSTRACT
In this dissertation, forging process design has been investigated with the primary
concern on risk reduction. Different forged components have been studied, especially
those ones that could cause catastrophic loss if failure occurs. As an effective modeling
methodology, finite element analysis is applied extensively in this work. Three examples,
titanium compressor disk, superalloy turbine disk, and titanium hip prosthesis, have been
discussed to demonstrate this approach.
Discrete defects such as hard alpha anomalies are known to cause disastrous failure if
they are present in those stress critical components. In this research, hard-alpha inclusion
movement during forging of titanium compressor disk is studied by finite element
analysis. By combining the results from Finite Element Method (FEM), regression
modeling and Monte Carlo simulation, it is shown that changing the forging path is able
to mitigate the failure risk of the components during the service.
The second example goes with a turbine disk made of superalloy IN 718. The effect of
forging on microstructure is the main consideration in this study. Microstructure defines
iii
the as-forged disk properties. Considering specific forging conditions, preform has its own
effect on the microstructure. Through a sensitivity study it is found that forging
temperature and speed have significant influence on the microstructure. In order to choose
the processing parameters to optimize the microstructure, the dependence of
microstructure on die speed and temperature is thoroughly studied using design of
numerical experiments. For various desired goals, optimal solutions are determined.
The narrow processing window of titanium alloy makes the isothermal forging a preferred
way to produce forged parts without forging defects. However, the cost of isothermal
forging (dies at the same temperature as the workpiece) limits its wide application. In this
research, it has been demonstrated that with proper process design, the die temperature can
be reduced greatly without violating process window constrictions. Moreover, the
computation cost is also reduced by replacing the complex 3-dimensional (3D) shape with
its corresponding 2-dimensional (2D) representative cross sections, and a well balanced
load distribution has been achieved by proper design of die flashland.
iv
Dedicated to my family
v
ACKNOWLEDGMENTS
This dissertation could not have been written without Dr. Rajiv Shivpuri, who not only
served as my advisor and provided me financial support, but also encouraged and
challenged me throughout my academic program. It is Dr. Shivpuri who guided me to
learn knowledge and the methodology to obtain it. The research experience working with
Dr. Shivpuri has helped me to become more professional and be prepared to make more
contributions to the future.
I would like to express my sincere appreciation to members of my dissertation committee
Dr. Jose M. Castro and Dr. Allen Yi for their scientific inputs and advices. I would also
like to thank members of my candidacy committee, Dr. Gary Kinzel, Dr. Henry Busby,
and Dr. Theodore Allen for their valuable comments and suggestions.
Thank also goes to my group members, Dr. Francesco Gagliardi, Dr. Chun Liu, Dr.
Yuanjie Wu, Dr. Xiaomin Cheng, Dr. Meixing Ji, Dr. Wenfeng Zhang, Dr. Jiang Hua, Dr.
Satish Kini, Dr. Sailesh Babu, Dr. Zhiqiang Sheng, Yijun Zhu and Kuldeep Agarwal for
their helpful discussions and friendship during my graduate program.
vi
I wish to thank my parents for their unconditional love and endless support throughout
my doctoral study. Finally, I would like to express my sincere gratitude to my wife Dr.
Ruomiao Wang for her continuous encouragement, love and never-ending patience.
vii
VITA
May, 1978 Born Shenyang, China
2000 B.S., Plasticity Engineering, Shanghai
Jiao Tong University, Shanghai, China
2000 2003 M.S., Mechanical Engineering, Shanghai
Jiao Tong University, Shanghai, China
2003 2009 Graduate Research Associate, Department
of Industrial, Welding, and Systems
Engineering, The Ohio State University
PUBLICATIONS
Rajiv Shivpuri, Xiaomin Cheng, Yongning Mao. Elasto-plastic pseudo-dynamic numerical model for the design of shot peening process parameters. Materials and Design, in press.
FIELDS OF STUDY
Major Field: Industrial and Systems Engineering
Minor Fields: Operations Research and Design Optimization
viii
TABLE OF CONTENTS
ABSTRACT........................................................................................................................ ii
ACKNOWLEDGMENTS .................................................................................................. v
VITA ................................................................................................................................. vii
LIST OF FIGURES .......................................................................................................... xii
LIST OF TABLES ........................................................................................................... xvi
CHAPTER 1 INTRODUCTION ........................................................................................ 1
1.1 Forging processes ......................................................................................... 1
1.1.1 Applications of forged parts.................................................................... 2
1.1.2 Classification of forging processes ......................................................... 3
1.2 Tooling and process design issues................................................................ 5
1.3 Risk and forging ........................................................................................... 8
1.4 Objective and outline ................................................................................. 14 CHAPTER 2 BACKGROUND AND LITERATURE REVIEW..................................... 17
2.1 Preform design in forging process.............................................................. 18
2.1.1 Backward finite element simulation ..................................................... 18
2.1.2 Sensitivity analysis approach................................................................ 23
2.1.3 Other approaches .................................................................................. 27
2.2 Property control in titanium forging........................................................... 29
2.2.1 Metallurgy of conventional titanium alloys .......................................... 30
2.2.2 Hot working of titanium alloys ............................................................. 32
2.2.3 Related work on forging of titanium alloys .......................................... 38
2.3 Property control in superalloys forging...................................................... 46
2.3.1 Metallurgy of superalloys ..................................................................... 47
2.3.2 Melt-related defects in superalloys ....................................................... 48
ix
2.3.3 Forging of superalloys .......................................................................... 53
CHAPTER 3 APPROACH AND METHODOLOGY...................................................... 58
3.1 Finite element method ................................................................................ 58
3.1.1 Rigid-plastic FEM................................................................................. 60
3.1.2 Metal forming modeling using viscoplastic approach .......................... 62
3.1.3 Applications in forging ......................................................................... 63
3.2 Design of experiments and response surface methods............................... 65
3.3 Monte Carlo simulation.............................................................................. 70
CHAPTER 4 EFFECT OF FORGING PATH ON MICROFEATURE LOCATION IN COMPRESSOR DISK FORGING................................................................................... 72
4.1 Introduction to hard alpha inclusion........................................................... 72
4.2 Multi-body simulation modeling................................................................ 75
4.2.1 Constitutive equations and friction ....................................................... 75
4.2.2 Spatial and time discretization .............................................................. 77
4.2.3 Discrete contact treatment..................................................................... 78
4.2.4 Finite element formulation.................................................................... 79
4.3 Titanium forging modeling with hard alpha inclusion ............................... 80
4.3.1 3D modeling of hard alpha in forging................................................... 81
4.3.2 Simplification of 3D modeling to 2D modeling ................................... 94
4.4 Risk mitigation by changing forging paths ................................................ 95
4.4.1 Forging path selection and constraints.................................................. 97
4.4.2 Numerical simulations to build regression models............................. 100
4.4.3 Stochastic simulations for risk evaluation .......................................... 103
4.4.4 Further investigation on other possible paths ..................................... 109
4.5 Summary and conclusions.........................................................................112
CHAPTER 5 MICROSTRUCTURE CONTROL IN TURBINE DISK FORGING ......114
5.1 Modeling microstructure in hot working ..................................................114
x
5.1.1 Microstructure evolution during forging .............................................114
5.1.2 Microstructure modeling of superalloys ..............................................115
5.1.3 Microstructure model validation for IN 718........................................119
5.2 Effects of forging path design on microstructure of disk forging ............ 120
5.2.1 Various forging path designs............................................................... 121
5.2.2 Risk associated with microstructure ................................................... 123
5.2.3 Microstructure comparison for different forging paths....................... 125
5.3 Effects of forging parameters on microstructure of disk forging ............. 131
5.3.1 Different combinations of temperature and die speed ........................ 131
5.3.2 Analysis of simulation results............................................................. 132
5.3.3 Optimization of forging parameters for various objectives ................ 139 5.4 Summary and conclusions........................................................................ 144
CHAPTER 6 APPLICATION TO TITANIUM HIP IMPLANT FORGING ................. 146
6.1 Introduction .............................................................................................. 146
6.2 Problem definition and constraints........................................................... 150
6.3 Methodology and Procedure .................................................................... 152
6.3.1 Material modeling............................................................................... 152
4.3.2 Thermal data ....................................................................................... 153
4.3.3 Material instability .............................................................................. 153
6.3.4 Geometry simplification ..................................................................... 155
6.3.5 Process variables................................................................................. 157
6.4 Results and Discussion............................................................................. 159
6.4.1 Simulation results................................................................................ 159
6.4.2 Relation to risk.................................................................................... 172
6.5 Summary and conclusions........................................................................ 172
CHAPTER 7 CONCLUSIONS AND FUTURE WORK ............................................... 174
xi
7.1 Summary and conclusions........................................................................ 174
7.2 Suggestions for future work ..................................................................... 176
APPENDIX..................................................................................................................... 178
APPENDIX A. 70 points microstructure information........................................... 178
LIST OF REFERENCES................................................................................................ 191
xii
LIST OF FIGURES
Figure 1.1 Process of (a) open die forging and (b) impression-die forging........................ 4 Figure 1.2 Example risk profile .......................................................................................... 9
Figure 1.3 Thermal-mechanical fatigue cracking and oxidation in a turbine blade ..........11
Figure 1.4 Creep crack in a turbine vane .......................................................................... 12
Figure 1.5 Low cycle fatigue results for U 720 LI at 600 C ........................................... 12
Figure 1.6 Effect of grain size on creep strength of IN 100.............................................. 13
Figure 1.7 Broken disk caused by fatigue crack emanating from hard alpha................... 13
Figure 1.8 General procedure to reduce risk by forging process design .......................... 15
Figure 2.1 Concept of the backward tracing scheme........................................................ 21
Figure 2.2 Flow chart of shape sensitivity method ........................................................... 26
Figure 2.3 Phase diagram used to predict results of forging or heat treatment practice... 33
Figure 2.4 Microstructure developed in Ti-6Al-4V by different forging temperature ..... 34
Figure 2.5 Comparison of mechanical properties achieved in + and forged titanium alloys ................................................................................................................................. 35
Figure 2.6 Typical stress strain curves for titanium alloys ............................................... 39
Figure 2.7 Power dissipation efficiency map and instability map obtained on Ti-6Al-4V ........................................................................................................................................... 41
Figure 2.8 Stress-rupture strength of superalloys ............................................................. 47
Figure 2.9 Solidification segregation evident as grain size and second phase particle banding in wrought Alloy 718 .......................................................................................... 49
Figure 2.10 Large freckles on transverse and longitudinal alloy 718 billet slices from a 710 mm diameter ingot ............................................................................................................ 50
Figure 2.11 Large discrete white spot in an alloy 718 billet slice. Scale in inches........... 51
Figure 2.12 Surface cracking caused by poor forging practice......................................... 54
Figure 2.13 Fully recrystallized grains and microstructure with many unrecystallized
xiii
grains in IN-718 ................................................................................................................ 54
Figure 2.14 IN-718 microstructure showing grain-size bands caused by too high a forging temperature ....................................................................................................................... 55
Figure 3.1 Different types of material stress-strain curves ............................................... 59
Figure 3.2 Advantages of using FE simulations in forging .............................................. 64
Figure 4.1 Typical hard alpha inclusion............................................................................ 73
Figure 4.2 segregation: voids surrounded by stabilized ............................................ 74
Figure 4.3 3D multi-body model of upsetting .................................................................. 82
Figure 4.4 Compression stress-strain curves of hard alpha Ti .......................................... 84
Figure 4.5 Ti-6Al-4V flow data for 950C from Seshacharyulu et al. ............................. 85
Figure 4.6 Global equivalent strain distribution of forged part in Case 1 ........................ 86
Figure 4.7 Global equivalent strain distribution of forged part in Case 2 ........................ 86
Figure 4.8 Global equivalent strain distribution of forged part in Case 3 ....................... 87
Figure 4.9 Global equivalent strain distribution of forged part in Case 4 ........................ 87
Figure 4.10 Local equivalent strain distribution on inclusion in Case 1 .......................... 88
Figure 4.11 Local equivalent strain distribution on inclusion in Case 2........................... 89
Figure 4.12 Local equivalent strain distribution on inclusion in Case 3 .......................... 89
Figure 4.13 Local equivalent strain distribution on inclusion in Case 4 .......................... 90
Figure 4.14 Points selected for comparison...................................................................... 91
Figure 4.15 Defects exceedance curve (1106 kg) for titanium rotor disk materials ....... 93 Figure 4.16 Titanium disk forging and machined disk ..................................................... 96
Figure 4.18 Strains to initiate cavities and fracture for Ti-6Al-4V................................... 98
Figure 4.19 Different forging paths and point positions................................................... 99
Figure 4.20 Points in slot area to be back tracked to billet ............................................. 101
Figure 4.21 Points tracked back to billet for different forging paths .............................. 102
Figure 4.22 Monte Carlo sample points distribution in billet......................................... 104
Figure 4.23 Strategy to relate failure risk with applied stress......................................... 106
xiv
Figure 4.24 Failure probability assumed for slot area .................................................... 107
Figure 4.25 Determination of feasible region ..................................................................111
Figure 4.26 Failure rates for different forging path with standard deviation...................112
Figure 5.1 Superalloy disk forging and machined disk .................................................. 121
Figure 5.2 Cross section of forging and machined part .................................................. 122
Figure 5.3 Three different forging paths ......................................................................... 123
Figure 5.4 Low cycle fatigue results for U 720 LI at 600C .......................................... 124
Figure 5.5 Effect of grain size on creep strength of IN 100............................................ 124
Figure 5.6 Machined disk and 14 zones to check microstructure................................... 126
Figure 5.7 Distribution of checking points ..................................................................... 126
Figure 5.8 Grain size distribution for different preforms ............................................... 129
Figure 5.9 Fraction of recrystallization for different preforms....................................... 130
Figure 5.10 Fraction of recrystallization for different temperatures with V=5 mm/s..... 134
Figure 5.11 Fraction of recrystallization for different die speeds with T=920C........... 135
Figure 5.12 Grain size for different temperatures with V=5 mm/s................................. 136
Figure 5.13 Grain size for different die speeds with T=5 mm/s ..................................... 137
Figure 5.14 Rim grain size dependence on temperature and die speed .......................... 138
Figure 5.15 Overall grain size dependence on temperature and die speed ..................... 139
Figure 5.16 objective1 as function of die speed.............................................................. 142 Figure 5.17 objective2 as function of die speed.............................................................. 142 Figure 5.18 objective3 as function of die speed.............................................................. 143 Figure 5.19 objective4 as function of die speed.............................................................. 143 Figure 6.1 a) Commercial hip; b) Material distribution along the hip axis .................... 151 Figure 6.2 Instability map for Ti-6Al-4V with microstructural observations in the - regime at a strain of 0.5................................................................................................... 154
Figure 6.3 2D cross sections to be studied...................................................................... 156
Figure 6.4 Location of critical area and cross-section .................................................... 156
xv
Figure 6.5 Flow chart of followed approach................................................................... 157
Figure 6.6 Integration modelling of the hot working process......................................... 159
Figure 6.7 Strain distribution of symmetrical preform and unsymmetrical preform...... 160
Figure 6.8 Thickness measurement to validate the reliability of the process ................. 161
Figure 6.9 Strain rate distribution in the critical zone .................................................... 163
Figure 6.10 The thickness of unstable material (temperature lower than 800C) .......... 163 Figure 6.11 Temperature and strain rate distribution after preforming with performing die temperature of 200C a) temperature before cooling, b) temperature after cooling, c) strain rate................................................................................................................................... 164
Figure 6.12 Temperature distribution before and after load adjustment for B-B and C-C section ............................................................................................................................. 166
Figure 6.13 Preforming stage a) before forging, b) after forging ................................... 166 Figure 6.14: Temperature comparison for C-C section in preforming stage a) 2D simulation, b) 3D simulation ............................................................................................................. 167 Figure 6.15 Temperature comparison of C-C cross section in final forming stage between 2D simulation and 3D simulation ................................................................................... 168
Figure 6.16 Temperature distribution on the hip implant at the end of the forging process......................................................................................................................................... 169
Figure 6.17 Die wear on preforming die and finishing die............................................. 170
Figure 6.18 Die stress on preforming die and finishing die............................................ 171
Figure A.1 Checking points and coordinate system of machined disk ........................... 178
xvi
LIST OF TABLES
Table 1.1 Main forging parameters and their effects .......................................................... 8
Table 2.1 Properties comparison between + and forging.......................................... 36 Table 4.1 Final positions of tracked points in 3D simulations.......................................... 91
Table 4.2 Stress and strain of tracked points in 3D simulations ....................................... 91
Table 4.3 Final position comparison for small inclusion.................................................. 92
Table 4.4 Comparison of point locations, strains and stresses in 2D and 3D simulations 95
Table 4.5 Max load and strain for four different forging paths in finishing step............ 100
Table 4.6 Calculated failure rate for four different forging paths ................................... 108
Table 4.7 Max load and strain for various forging paths in finishing step ..................... 109
Table 4.8 Calculated failure rate for five different forging paths ....................................111
Table 5.1 Modeling constants for IN 718 ........................................................................119
Table 5.2 Model validation results 1 (compare to Zhou and Baker [1995])....................119 Table 5.3 Model validation results 2 grain size (compare to Medeiros et al. [2000]) .... 120 Table 5.4 Average grain size/standard deviation for 3 preforms..................................... 127
Table 5.5 Design matrix with different temperature and die speed ................................ 131
Table 5.6 Average grain size/standard deviation for different forging conditions.......... 132
Table 5.7 Results for different objectives ....................................................................... 141 Table 6.1 Maximum thickness of unstable material at the end of process with same temperature of preforming die and finishing die ............................................................ 161
Table 6.2 Maximum thickness of unstable material at the end of process with different temperature of preforming die and finishing die ............................................................ 162
Table 6.3 Forging loads in different cross sections......................................................... 165
Table A.1 Coordinates of checking points ...................................................................... 179
Table A.2 Microstructure information T=950C V=5 mm/s preform 1.......................... 180
xvii
Table A.3 Microstructure information T=950C V=5 mm/s preform 2.......................... 181
Table A.4 Microstructure information T=920C V=5 mm/s preform 3.......................... 182
Table A.5 Microstructure information T=920C V=20 mm/s preform 3........................ 183
Table A.6 Microstructure information T=920C V=50 mm/s preform 3........................ 184
Table A.7 Microstructure information T=950C V=5 mm/s preform 3.......................... 185
Table A.8 Microstructure information T=950C V=20 mm/s preform 3........................ 186
Table A.9 Microstructure information T=950C V=50 mm/s preform 3........................ 187
Table A.10 Microstructure information T=980C V=5 mm/s preform 3........................ 188
Table A.11 Microstructure information T=980C V=20 mm/s preform 3...................... 189
Table A.12 Microstructure information T=980C V=50 mm/s preform 3...................... 190
1
CHAPTER 1
INTRODUCTION
1.1 Forging processes
As one of the earliest metal working processes, forging has had a long history of
development. But not until the last century did forging make a remarkable progress due to
advancement of science and technology, which provided demands as well as technologies
to improve the forging technique. Today, forging still plays an important role in providing
parts and products that influence our modern lifestyle. According to annual report of
Forging Industry Association [ www.forging.org ], the 2007 custom impression die forging
industry sales was 6,149.8 million dollars, an increase of 25% compared to that in 2004.
Automotive industry made up 30.3% share of the total forging market, and aerospace
applications contributed 26.6%. The industry sales of custom open die forgings increased
to 1,786.9 million dollars, which doubled the figure in 2004.
Forging is known as a secondary manufacturing process, which converts the products from
the primary operation into semi-finished or finished parts. During forging, metal is
2
squeezed or compressed under high pressure to form the products. The deformation it
undergoes gives the forged parts superior mechanical properties by aligning materials
structure along the direction of deformation, eliminating the cast dendritic structure and
sometimes developing a fine-grained structure as a result of recrystallization. Compared to
casting, forging is stronger and has a better response to heat treating. Compared to
machining, forging has a wider size range of desired material grades and a preferable grain
orientation along surface; besides, forging makes a better use of materials with the material
savings as great as 75% compared to machining [SCHULER GmbH, 1998]. In cold and
warm forging, it is possible to use a lower-cost steel grade since the strain hardening, which
occurs during forming, can improve both ultimate and fatigue strength. Thus, forging is
preferred in applications where reliability, strength, fatigue resistance and economy are
critical.
1.1.1 Applications of forged parts
The main applications of forged parts are in the automotive and the aerospace industries.
More than 250 forgings can be found in a typical car or truck; most of these parts
experience large stress and shock, such as connecting rods, crankshafts, transmission shafts
and differential gears. Some aircrafts even contain more than 450 structural forgings as
well as hundreds of forged engine parts. The high standard of reliability and performance
reliability and performance has made both the ferrous and the nonferrous forgings the right
choice for aerospace area. Considering the required material properties, high specific
3
strength materials like titanium alloys can increase the payloads as well as range and
performance. Nickel-based and cobalt-based superalloys are widely used in turbine engine
components for the superior mechanical properties in high temperature. Other industrial
applications of forged parts are also found in agricultural machinery, off-highway
equipment, industrial equipment, ordnance and oil field equipment.
1.1.2 Classification of forging processes
Based on how metal flow is confined, forging can mainly be classified as open die forging
and impression-die forging (Figure 1.1). Open die forging is performed between two flat or
near flat dies, with no side wall in the tooling so that the metal can flow freely in lateral
direction. Open die forging can produce disks, blocks, bars, step shafts, etc. The main
advantage of open die forging is the large size of the parts it can produce: forgings up to
more than 150 tons can only be produced by the open die forging process. In
impression-die forging, two or more die blocks with negative shapes are brought together
to form a cavity, in which the metal being deformed undergoes plastic deformation. As the
metal flow is confined by die impression, impression-die forging can yield more
complicated shapes and closer tolerances than open die forging. The flash formed during
forging increases the pressure in cavity, thus helps the filling of even the most complex
detail. These advantages make impression-die forging predominant in the forging industry.
4
(a)
(b)
Figure 1.1 Process of (a) open die forging and (b) impression-die forging
Flashless forging can be considered as a form of impression-die forging. No excess metal
escapes the die cavity at the end of the stroke, this improves material utilization. The
workpiece volume and die must be precisely controlled to ensure filling of the die cavity
without generation of excessive die load. Net-shape forging and near-net forging can
further reduce the wastage of material by significantly reducing or eliminating subsequent
machining.
Depending on the temperature at which metal is forged, forging can be classified as cold
forging, warm forging and hot forging. Cold forging is always performed at room
temperature with the use of an interface lubricant. The high precision of cold forged parts,
sometimes even draftless, enables their use with little finishing. Hot forging is conducted
above the recrystallization temperature so that no strain hardening occurs and metal flow
5
stress is much lower. Improved metal flow ensures a more complex shape and more
deformation. Most starting billets have to be hot forged in order to achieve a large shape
change. With the advantages similar to cold forging, warm forging is carried out at a higher
temperature than cold forging but still lower than recrystallization temperature.
In hot-die forging, a form of hot forging, dies are heated to a higher temperature than room
temperature to help the metal flow. Similarly, isothermal forging is usually performed
using a die with the same temperature as metal being worked. They are usually employed
to forge alloys, which are temperature sensitive and difficult to forge, like titanium alloys
and superalloys. Vacuum or protection atmosphere is usually used in isothermal forging to
avoid oxidation of the die materials.
1.2 Tooling and process design issues
From the perspective of technology, the increasing global competition in forging industry
comes from processes and materials [Barnett, 2000]. The improvement in the processes
and the development of the new processes make it possible to enhance the quality of
forgings, reduce the cost and increase productivity. The advances in forging and supporting
equipment provide the basis for the process improvements. Forging produces closer
tolerance, smaller draft angle and less flash; net and near-net forging technology is being
combined with the advanced materials to achieve complex shape with minimum cost;
some parts are able to be used after little or no subsequent processing. Forging research
6
also focuses on new materials since they give superior performance in their application
field. Titanium alloys, aluminum alloys, superalloys and other difficult-to-fabricate alloys
have different properties with steels so that research must be conducted to produce sound
products. For some superalloys, titanium alloys, and aluminum alloys, specifically
designed and controlled thermomechanical processing (TMP) technology has been used to
produce products with the best possible mechanical properties and optimum forging
microstructural uniformity [Thomas et al., 1985].
The main problems that most forging industries face include:
Forging defects like underfills, folds, and cracks, which lead to the scrap when they
exceed certain limit;
The metallurgical qualities of forgings are not sufficiently good to yield the desired
mechanical properties. The metallurgical quality problems may encompass: excessive
grain growth, non-uniformity of microstructure, and out-of-controlled phase, etc.;
Die failure due to excessive die wear and die softening.
Die design and forging parameter design are two major parts in forging process design.
Final die design depends on forging design, which includes finish allowance, forging draft,
parting-line location, flash, and fillet. Final die design is not a concern in this research.
Forging is usually considered as a multiple-sequence process because most forgings cannot
be produced in one operation. Generally, a forging produced prior to the final forging
7
operations is called a preform. Preform design is usually an important part of forging die
design. Two main reasons to use preform are: the metal cannot flow smoothly to fill the die
cavity completely; and the metal flow and stress are so high that finisher die will wear
quickly [Vemuri, 1986]. Design of forging parameters mainly includes temperature at
which the metal is deformed, die temperature and die velocity.
A well designed preform can remove defects, reduce die load and obtain the required strain
distribution in forgings. The preheating temperature will influence the forging load,
temperature distribution and metal flow. Die temperature mainly influences the
temperature distribution and forging load. If isothermal forging is used, the cost is
significantly higher than conventional forging. Die velocity mainly influences strain rate;
however, temperature distribution is also a result of die velocity because of the heat
generation and dissipation during deformation and heat transfer between workpiece and
tools. The main design parameters and their effects are listed in Table 1.1. As these
parameters will change the strain, strain rate, temperature and metal flow, process design
can lead to different microstructure in forgings; thus by proper design of forging process,
desired mechanical properties can be obtained.
8
Design parameters Effects/responses
Die design/preform design Forging feasibility, strain distribution Billet temperature Temperature, metal flow, load
Die temperature Load, temperature distribution, cost
Die velocity Strain rate, temperature distribution
Table 1.1 Main forging parameters and their effects
1.3 Risk and forging
Before the introduction to risk, the definitions of hazards and event consequences must be
given. A hazard is a source of harm, and can be defined as a phenomenon or act posing
potential harm to some person and its potential consequences. Failure event consequences
are the degree of damage or loss from some failure. Risk can be defined as the potential
losses resulting from an exposure to a hazard or as a result of a risk event [Ayyub, 2003].
Risk can be linked to uncertainties associated with events.
Most commonly, risk is measured as the likelihood of occurrence of the event and
consequences associated with the event. It can be described by the following equation:
)],),...(,(),...,,(),,[( 2211 nnii cpcpcpcpRisk (1.1)
where pi is the probability of occurrence of event i, and ci is the consequence of this event.
Similarly, risk is also evaluated as product of likelihood of occurrence and impact severity
9
of the occurrence of the event [Ayyub, 2003]:
=
EventeConsequencIMPACT
TimeEventLIKELIHOOD
TimeeConsequencRISK (1.2)
In equation (1.2), risk is presented as an expected value of loss. Likelihood can be
expressed as a probability. A risk profile, also called Farmer curve, is a plot of occurrence
probabilities and consequences, as exemplified in Figure 1.2. In this figure, abscissa
represents the number of fatalities, and ordinate represents annual frequency of occurrence.
Risk profiles can also be constructed using probabilities instead of frequencies, and
economical losses instead of fatalities.
Figure 1.2 Example risk profile [Ayyub, 2003]
10
Forging and risk can be related by the failure of component manufactured by forging. For
example, a defect in a forged component of aircraft engine may increase the likelihood of
engine failure, which in turn, increases the risk of aircraft crash. As a forging engineer, one
cannot control the exposure to the activity involving accident risks, like aircraft flying time;
one cannot control the consequence of loss, either. The risk of component failure can be
mitigated by reducing the probability of forging failure through the proper design of
forging process.
In equation (1.2), impact is dependent on usage of parts so it cannot be controlled by
forging process design. The risk can be reduced by forging process design only by reducing
the likelihood of an event in equation (1.2). The likelihood of failure of a forged part can be
related to:
1) Microstructure and mechanical properties of a component;
2) Possible location of a discrete defect in the material.
The first factor can be exemplified in Figure 1.3 and Figure 1.4. Figure 1.3 shows the
fatigue crack in a turbine blade and Figure 1.4 shows a creep crack in a turbine vane. The
failures could be prevented if the mechanical properties, like fatigue strength and creep
rupture strength, are improved. It is well known that these properties can be influenced by
microstructure of the parts. The low cycle fatigue testing results of superalloy U 720 LI
11
(Figure 1.5) show that for fixed stress amplitude, materials with fine grains have longer
fatigue life than those with coarse grains. The creep strength property of superalloy IN 100
can be seen in Figure 1.6. Under the same testing conditions (same stress level and same
temperature), materials with larger grain size have a longer creep life than those with
smaller grain size. The dependencies of fatigue life and creep strength on grain size shown
here are valid for almost all metals. Therefore, forging process design, including preform
shape, temperature and forging speed etc., is able to change mechanical properties of
forged part by means of manipulating microstructure.
Figure 1.3 Thermal-mechanical fatigue cracking and oxidation in a turbine blade [Benac
and Swaminathan, 2002]
12
Figure 1.4 Creep crack in a turbine vane [Becker, 2002]
Figure 1.5 Low cycle fatigue results for U 720 LI at 600 C [Torster et al., 1997]
13
Figure 1.6 Effect of grain size on creep strength of IN 100 [Lasalmonie and Strudel, 1986]
The impact of second factor is seen in Figure 1.7. Discrete defect hard alpha in this
titanium disk led to fatigue failure. Proper forging process design may move the defect to
area which is subjected to lower stress or which will be removed by subsequent machining;
in turn, this reduces the probability of part failure.
Figure 1.7 Broken disk caused by fatigue crack emanating from hard alpha [Millwater and
Wirsching, 2002]
14
1.4 Objective and outline The objective of this dissertation is to develop a method to reduce the failure risk in critical
components via forging process design. First, numerical model is used to study the
deformation and movement of discrete defect in metal forming; the final location of defect
is then related to applied stress to find the severity of this defect. Second, the
microstructure of a forged part is manipulated by preform design, forging temperature and
forging speed to satisfy the requirements for mechanical properties. Finally, the forging
process design is made to reduce the cost of production of titanium hip implant. The work
in this research demonstrates the way that failure risk of forged parts can be reduced by
appropriate forging process design.
The general procedure of reducing risk of forged part is shown in Figure 1.8. For a
component, service conditions and mechanical requirements are analyzed; material
properties are then connected to component requirements; forging process design can
manipulate metal flow and microstructure evolution during forging to achieve the
objective of risk reduction.
15
Figure 1.8 General procedure to reduce risk by forging process design
This dissertation is organized as follows:
Chapter 1 gives the introduction of forging processes, design issues, the relation
between forging and risk and the dissertation outline.
Chapter 2 presents the background and literature review on forging process design,
especially preform design. Background of titanium alloys and superalloys (two kinds
of metals used in this dissertation) is also included.
Chapter 3 introduces the approaches and methodology used in this dissertation as part
of the research, such as Finite Element Method, Design of Experiments, and Monte
Carlo Simulation.
Chapter 4 studies the effect of discrete defect on forging failure risk. A titanium
16
compressor disk is used as an example to show that the forging path can be designed to
minimize the risk of failure due to hard alpha inclusion in a titanium billet.
Chapter 5 demonstrates that both preform design and process parameters have
influence on final microstructure of a turbine disk made of superalloy. For different
optimization objectives, microstructure in final forging can be optimized by proper
selection of forging parameters.
Chapter 6 shows the design procedure of hot die forging of titanium hip implant.
Lower die temperature is used to reduce the cost without introducing material defect
due to flow instability.
Chapter 7 summarizes this dissertation and provides comments of future work.
17
CHAPTER 2
BACKGROUND AND LITERATURE REVIEW
As one of the most common and modern metal-working processes, forging has
experienced greater development in recent years through continuous progress in many
areas, including [Forging Industry Association, 1997]:
Alloys are being developed and refined to improve processing characteristics;
Industrys understanding of the mechanics of the forging process is being increased by
growing manufacturing development in forging processes;
State-of-the-art equipment is being utilized to control critical processes;
As the usage of CAD/CAM throughout the design and production processes is
increasing, dimensional accuracy of forgings is improved and lead time is reduced;
Modeling and forging simulations are being used to minimize development time.
Based on the development achieved, research in forging continues seeking to make
improvements in process parameters, die design, equipment, materials, etc. Specifically,
18
research in this dissertation can be divided into two aspects:
1) Design of preform die shape aiming to improve the property of forging;
2) Determination of processing parameters to produce a defect free part as well as obtain
desired microstructure through thermomechanical processing.
A lot of related research work has been done in these two areas; some are reviewed in this
section.
2.1 Preform design in forging process
Preforms are traditionally designed by experience with no common rules that can be
summarized easily. Briefly, three basic guidelines for designing performs are [Altan et al.,
1973]:
1) Each cross section along length of preform must be equal to final cross section
expanded by flash area;
2) Preforms should have larger radii than that of finished parts;
3) In die closing direction, preform should be larger than finished forging if possible.
In the last two decades, various new methods have been employed to help preform design
to shorten the development period.
2.1.1 Backward finite element simulation
The FEM simulation has been widely used in metal forming processes to predict the metal
flow and formation of defects. The forging dies designed using empirical guidelines and
19
designers intuition can be verified by forward simulation, but they cannot be directly used
in forging die design. Intuitively, however, by inversely carrying out simulation from the
final forging to the initial preform, backward simulation can help us improve the preform
dies.
The idea of using backward simulation based on finite element method to design preforms
was first put forward by Park et al. [Part et al., 1983]. Unlike the normal finite element
method, which calculates stress and displacement step by step from the initial billet,
backward FE method traces the loading path in forging process inversely from a final
configuration. The calculation algorithm is illustrated in Figure 2.1. The left part of the
figure shows coordinate changes of a specific point, while the right part shows the iteration
process. The geometrical configuration at time t = t0-1 and t = t0 are x0-1 and x0, respectively,
and they are represented by point P and Q, respectively. The displacement needed in time
t is denoted by u0-1, so for forward path P to Q
x0 = x0-1 + u0-1 (2.1)
The backward problem is: given a known geometrical configuration Q (x0), the
geometrical configuration P is to be determined, so the problem is to calculate the
displacement at time t0-1, which is u0-1.
The backward tracing method is conducted in this way: Take forward solution at Q, which
is u0, a difference is calculated between x0 and u0 as the first estimate of point P, so
20
P(1) = x0 u0 (2.2)
Then the first estimate of forward displacement u(1)0-1 can be calculated based on point P(1).
The geometrical configuration in time t = t0 calculated from P(1), which is
Q(1) = P(1) + u(1)0-1 (2.3)
are then compared with the known configuration Q. If Q(1) and Q are close enough, P(1) is
taken as the P; otherwise, the second estimate of P are calculated by
P(2) = x0 u(1)0-1 (2.5)
The displacement field solution u(2)0-1 based on P(2) is then calculated and the second
estimate of Q, which is
Q(2) = P(2) + u(2)0-1 (2.6)
is then compared to Q. The iteration continues until
Q(n) = P(n) + u(n)0-1 (2.7)
is sufficiently close to Q. Since metal forming is a non-linear problem, the unknown path is
approximated by linear path within a sufficiently small step size. This deformation path can
be seen as a result of trial and error search.
21
Figure 2.1 Concept of the backward tracing scheme
A more detailed description in rigid-plastic and rigid visco-plastic FEM is made by Zhao et
al. [1995]. In backward simulation, there must be a criterion to detach the nodes from die
surface. Zhao et al. [1995] put forward a shape complexity factor based criterion. In this
method, shape complexity factor has been used to describe the complexity of axisymmetric
forging. The shape complexity factor increases from initial billet to final forging. When
metal enters the deep recesses and concaves with small radii, shape complexity factor and
forging load increase sharply. In forging process, it is favorable to have these regions filled
at the end of the stroke, so that the shape complexity factor increases sharply at the end.
Conversely, in backward simulation, it is better to have the shape complexity factor
decreased as fast as possible at the beginning steps.
22
So, iterations are used for every node that can be detached from the die, and the resulted
shape complexity factor is calculated. The node that causes the largest shape complexity
factor reduction is detached from the die. This criterion is only dependent on the
coordinates of boundary nodes and can be used to control both the top and bottom of the
workpiece. But since the shape complexity factor only describes the complexity of
axisymmetrical parts, this criterion is only suitable for axisymmetrical forging design.
An alternative node detachment criterion called inverse die contact tracking method was
proposed by Zhao et al. [1996]. Tool is divided into several linear or arc segments. A trial
preform, which probably does not meet the design objectives, is used in a forward
simulation, and the momentary times that each die segment comes into contact with the
preform are recorded. The boundary condition sequence obtained from trial forward
simulation must be modified to remove the defects formulated because the trial preform is
not the desired shape. A generic turbine disk die design using inverse die contact tracking
method was reported [Zhao et al., 1998]. By reducing the flash at the beginning of
backward simulation, this method can also be used to design a die cavity to achieve
flashless forging [Zhao et al., 2002]. Biglari et al. [1998] incorporated fuzzy logic into
backward deformation method to minimize defects and the strain range for an
axisymmetric part. In each backward time increment, the boundary nodes are released
according to strategy based on a fuzzy decision making method.
23
2.1.2 Sensitivity analysis approach
The gradient based method also draws lot of attention in preform design. In this method,
the derivatives of the objective function with respect to the design variables are calculated.
This usually involves the perturbation of the finite element equations. The design iteration
is then performed based on design sensitivity from those derivatives. This method is used
not only in shape design, but also in design of processing parameters.
Fourment and coworkers [1995] treated final forging die as known while the preform die
and the initial workpiece shape to be designed so that the objective, the difference between
shape actually achieved and desired shape, can be satisfied. BFGS algorithm, in which
gradient methods and sensitivity analysis have been employed, is used for optimizing both
preform and preforming die.
An optimization algorithm developed by Zhao et al. [1997a] to design preforming die uses
cubic B-spline curves to describe preforming die shape; the coordinates of the control
points are taken as design variables to minimize the shape difference between actual shape
and intended shape. In sensitivity analysis, the gradient of the objective function with
respect to design variables can be transformed to nodal displacement derivatives, the nodal
force derivatives and nodal velocity derivatives, so that it can be calculated eventually.
BFGS optimization algorithm is used to minimize objective. By die position compensation
in each time increment, volume of material could maintain constant to avoid volume loss
24
due to remeshing and geometry updating [Zhao et al., 1997b]. In a later publication, Zhao
et al. [2004a] modified the method to increase the computation efficiency.
Vieilledent and Fourment [2001] used direct differentiation of discrete equations to
calculate the derivatives of tool geometry, velocity and state variables with respect to the
shape parameters in axisymmetric problems. Better geometric conformity, homogenization
of deformation and minimization of folds are taken as objectives and BFGS algorithm is
used to solve the optimization problem. Later research [Do et al., 2004] even tested both
deterministic and stochastic optimization algorithms in 3D problems.
Srikanth and Zabaras [2000] introduced a continuum sensitivity analysis to calculate the
shape sensitivity of finite hyperelastic-viscoplastic deformation. Appropriate sensitivity
kinematics and constitutive problems were defined. The sensitivity analysis was performed
in an infinite-dimensional continuum framework. By utilizing finite element method,
direct deformation and sensitivity deformation problems were carried out. A fully implicit
algorithm was used for direct contact problem to improve accuracy of preform design for
more complex contact and frictional conditions.
Another optimization method based on a modified sequential unconstrained minimization
technique and a gradient method was developed by Castro et al. [2001]. Analytical
derivatives of objective function were considered to avoid expensive cost in calculating the
25
numerical derivatives. Based on the differentiation of the equations of the discrete problem,
the discrete derivatives of the objective function were calculated. The algorithm to solve an
inverse two-step forging is:
1) Finite element analysis of the preforming step is performed with an initial guess of
preforming die;
2) In every incremental time step, the sensitivities of the nodal velocities with respect to
design variables are obtained using the direct differentiation method;
3) After preforming stage, the sensitivities of the nodal velocities in the final stage are
updated;
4) When the final forging is finished, the gradients of the objective function can be
calculated using the sensitivities of nodal coordinates with respect to the design
variables;
5) If the stopping criteria are not met, optimization program will provide a new design
parameter vector;
6) Using the updated design parameters, optimization iteration continues until the
convergence conditions are satisfied.
The same optimization technique has been applied in 3D forging considering both
mechanical and thermal analysis by Sousa et al. [2002]. The goal of inverse problems is to
determine input data of direct problem so that a prescribed result can be obtained. The
authors intended to find an initial workpiece shape that can be forged to desired geometry
26
without excessive flash and underfill. A good agreement between simulation result and
designed geometry is reported.
Figure 2.2 Flow chart of shape sensitivity method [Shim, 2003]
Shim [2003] applied a sensitivity method in the preform design for 3D free forging. The
preform with a shape to be designed is to be forged by flat dies to produce a predetermined
shape. When the finite element analysis shows that initial preform does not yield desired
shape, an offset shape, which is produced by moving the nodes of the original shape, is
introduced. A second finite element analysis is carried out for the offset shape to produce
deformed offset shape. Shape sensitivities can be calculated by investigating how
offsetting of undeformed nodes influences the offsetting of deformed nodes. Based on the
shape error that represents how deformed geometry differs from target geometry, together
with shape sensitivity, a new set of points can be given as the preform. This process is
27
performed iteratively until the shape error is less than a preset value. This method can be
illustrated in flow chart shown in Figure 2.2. The method is used to eliminate barreling of
free surface in upsetting of circular cylinder, elliptical cylinder, clover shaped cylinder,
rectangular prism and stepped rectangular prism; the results demonstrate that the shape
sensitivity method provides excellent prediction of preform shape.
2.1.3 Other approaches
Kim and Chitkara [2001] used upper bound elemental technique (UBET) to analyze the
metal flow in forging of crown gear. Based on UBET analysis, several preforms were
designed in order to make the inner corner and outer corner to be filled simultaneously.
Preform design using UBET to achieve a complete die fill for both 2D and 3D were
reported [Bramley, 2001]. It provides rapid but approximate simulation and preform design,
which can be used as precursor for more accurate finite element simulations.
Lapovok and Thomson applied a strategy described as step backward, step forward for
rough draft design followed by step-by-step forward for finish design [Lapovok and
Thomson, 1995]. This method includes: choosing main parameters defining the shape,
determining preform shape according to selected parameters, choosing criteria for
optimization, solving the plasticity boundary problem and investigating the extreme value
of objective function to determine optimal parameters. The same strategy was applied to
minimize die damage accumulation by changing preform [Lapovok, 1998].
28
Tomov and Radev [2004] created a criterion based on their shape complexity factor to
decide if a preforming step is necessary. The application of this criterion reduces the tool
cost by eliminating unnecessary preforming stages as well as reduces die wear by avoiding
excessive deformation in one forging step.
Oh and Yoon [1994] applied low pass filtering method in preform design. The preform
geometries can be obtained by expanding the finisher geometry in terms of Fourier series
and eliminating the high frequency terms. Some modifications are needed according to
conventional preform design. This method was used in 3D forging [Oh et al., 2004].
Similar method can be found in the work done by Lee et al. [2002]. It is observed that the
equi-potential lines generated between two conductors of different voltages show similar
trends for the minimum work path between the undeformed shape and deformed shape.
Thus, the equi-potential lines obtained by the arrangement of the initial and final shapes are
utilized to design the preform.
When the derivative based approach may not be applicable, direct search approach such as
genetic algorithm can be used. In the work done by Chung and Hwang [2002], genetic
algorithm has been used to optimize the objective functions, which are minimum unfilled
die cavity when material starts to form the flash and uniform temperature in the work, by
changing preforming die shape. An integrated thermal-mechanical element model was
29
used to conduct forging calculations. Similar approach was used by Castro et al. [2004] to
optimize the shape and energy consumption during forging by varying the shape and
temperature of workpiece before forging.
Researchers also proposed and applied an iterative preform design technique to reduce
forging volume [Hong et al., 2006]. A boundary region at the outlet of the flash was
selected in initial FEM simulation. This region was traced back along the deformation path
to initial billet; the initial shape was updated by removing this excessive section and the
new shape was used in the next simulation. This approach can remove the excessive flash
and thus reduce the tool load and tool wear. To achieve the same goal, a new approach has
been proposed recently by coupling finite volume method (FVM) and parametric design
method [Sedighi and Tokmechi, 2008]. Reduction on cost and time in the stages of
designing and improving preform is claimed by authors.
2.2 Property control in titanium forging
Titanium and titanium alloys have been used widely in aerospace industry, chemical
industry and energy industry for their high strength-to-weight ratio, outstanding corrosion
resistance and excellent mechanical properties. The current level of performance, airframe
strength, speed, range and other critical factors of aircrafts can only be achieved with the
application of titanium alloys in aircraft engines, airframes and other components. These
strong, light, corrosion resistant metals are also extremely suitable for implant purposes as
30
they possess exceptional biocompatible property. Titanium bone and joint replacements,
dental implants, cardiovascular devices and other parts are produced and used for medical
purposes worldwide every year. The properties of titanium alloys are primarily determined
by the metallurgical features, which is a result of composition and processing history.
2.2.1 Metallurgy of conventional titanium alloys
There are two crystalline forms that exist in pure titanium: hexagonal close packed (hcp)
phase at low temperature and body centered cubic (bcc) phase at an elevated temperature.
The temperature at which transition from to occurs (about 882 C for pure titanium) is
called transus.
All technologically important forms of titanium contain deliberate alloying additions
[Williams, 1995]. These additions affect the phase equilibria and microstructure by way of
altering the relative thermodynamic stability of phase and phase. According to how the
alloying elements influence the transus, these elements can be classified as and
stabilizers, and neutral elements. The and stabilizers have a tendency of concentrating
in either or phase, respectively, which is called solute partitioning. The volume fraction
of the more stable phase is stabilized by adding these alloying elements.
Conventional titanium alloys are commonly categorized as alloys, alloys and +
alloys according to which phase are predominantly present at room temperature under
31
normal conditions. The latter two alloys have higher strength and are easier to shape and
work. Nowadays, the most commonly used titanium alloys are + alloys; among them,
Ti-6Al-4V constitutes the largest portion of all Ti alloy usage.
An interesting observation is that the strength of the two phase mixture in + alloys is
considerably higher than either or alloys even in annealed condition. This synergism
has significantly increased technical interest in using titanium alloys for light weight
structures. Recently, the usage of alloys in many fields such as aircraft and petrochemical
equipment are growing rapidly. However, the total volume is still small compared to +
alloys because of the reasons ranging from producibility to changes in design philosophy
considering fracture toughness, strength, and other properties.
When or alloys are mentioned, that does not mean the other phase is totally absent in
the material. In fact, alloys are usually used in aged condition, in which some of phase
is present as strengthening precipitate. On the contrary, a small amount of phase in
alloys can be considered beneficial because it increases hydrogen tolerance and acts as
grain refining constituent.
Thermomechanical processing (TMP) is able to produce a variety types of microstructure
in a single alloy that may not be available by using heat treatment alone. By using TMP,
microstructures of titanium alloys can be controlled to balance strength and ductility. TMP
32
of + alloys can be divided into two categories: + processing and processing. This
depends on the temperature range at which the working operation is completed. Working in
+ range below transus produces phase characterized by equiaxed microstructure,
which is known as primary . The volume fraction of primary varies according to
different finishing temperatures and subsequent heat treatment. In forging, colonies of
plates develop and grain boundary phase exists on prior grain boundaries. The
boundary is deleterious to mechanical properties and is desired to be removed.
2.2.2 Hot working of titanium alloys
Nowadays, titanium alloy components can be manufactured by all kinds of forging
methods. Titanium forgings may be superior to bar or other forms in all tensile strength,
fatigue strength, creep resistance, and toughness [Donachie, 2000]. The mechanical
properties and microstructure of the forgings are greatly influenced by the working history
and forging parameters. For + alloys, the forging temperature relative to transus, the
plastic strain rate and the amount of deformation influence the microstructure of forgings;
this is true for both as-forged parts and microstructural changes occur during post-forging
heat treatments [Williams, 1995]. Over-exposure of titanium alloys to high temperature
should be avoided since it can cause the formation of excessive scale and increase the
formation of phase due to interaction with the interstitial elements oxygen and nitrogen.
The forging pressure depends on composition, temperature, strain rate, and process and
varies over a large range. However, a higher stress is required than that in the processing of
33
steels.
Figure 2.3 Phase diagram used to predict results of forging or heat treatment practice
[Donachie, 2000]
Most of secondary hot working of titanium alloys are performed in + phase range
[Semiatin et al., 1997]. Both and phases exist in the microstructure at all times. The
amount of each phase during the forging process depends upon the temperature distance
from transus. Figure 2.3 illustrates how the percentage of each phase changes during the
forging or heat treatment for Ti-6Al-4V. The microstructure after + forging is
characterized by deformed or equiaxed in a transformed matrix as shown in Figure 2.4
(a). The microstructure detail is determined by the amount of deformation at various
temperatures and the plastic strain rate. Thus, the uniform distribution of strain and strain
34
rate determines the uniformity of the microstructure.
(a) + processed (b) processed
Figure 2.4 Microstructure developed in Ti-6Al-4V by different forging temperature
[Williams, 1995]
Compared to + forging, forging is a relatively less common method in secondary
processing. The acicular or Widmanstatten (Figure 2.4 (b)) is developed and this
structure has better toughness, fatigue crack propagation resistance and creep resistance.
During the cooling followed by forging, forms on the prior grain boundary. To
remove undesirable grain boundary , it is a good practice to work continuously through
transus temperature. This results in continuous recrystallization of phase and little or no
grain boundary formation [Williams, 1995]. Because of the high temperature and the
formation of new grains by recrystallization every time the transus is exceeded, the
35
influences of deformation in forging are not necessarily cumulative. A significantly
lower pressure is required for forging and the cracking tendency is reduced; while
non-uniform working and excessive grain growth may cause variant properties inside the
parts.
The comparison of two forging approaches of different + alloys in strength can be seen
in Figure 2.5. A qualitatively comparison of + forging and forging is made in Table
2.1.
Figure 2.5 Comparison of mechanical properties achieved in + and forged titanium
alloys [Donachie, 2000]
36
Properties + forging forging Yield strength X
Creep strength X
Fatigue initiation X
Fatigue crack growth resistance X
Fracture toughness X
Ductility and formability X
hot salt stress corrosion cracking resistance X
Aqueous stress corrosion cracking resistance X
Hydrogen tolerance X
Table 2.1 Properties comparison between + and forging [Davis, 1998; Donachie,
2000]
Hot die isothermal forging is an advanced technology in working titanium alloys. Since the
die temperature is the same as the workpiece, absence of heat transfer between tool and
titanium makes flow stress constant. The microstructure can be controlled better and the
property variation is minimized. To protect the tools, which are commonly made of TZM, a
Mo based alloy, closed chamber with inert gas environment is utilized. This imposes a
limitation in forging size and production cost.
For + titanium alloys, ensuring the sufficient workability is as important as controlling
the microstructure and texture. Workability becomes a major issue during subtransus hot
working. Fracture-related defects, shear-localization defects and gross metal flow defects
are included in workability issue [Semiatin et al., 1997].
37
Defects related to fracture are created by large stress concentrations at grain boundaries
caused by microscopically inhomogeneous deformation. When high strain rate is imposed,
diffusion or plastic flow cannot relieve the stress, thus gaps are formed in the metal.
Various researchers revealed that workability can be significantly improved if high
temperature and low strain rate are applied simultaneously during hot working.
In conventional hot forging, the metal close to tools is more susceptible to heat loss and
undergoes less deformation than metal inside. Shear-localization defects such as shear
cracks and shear bands tend to develop between low deformation zones and high
deformation zones. Forging speed is the most prominent process variable, which
influences the shear band severity in conventional hot forging by affecting the processing
time and heat transfer. Excessive slow working rate may lead to the workpiece temperature
drop into lower workability region and cause cracking along the shear bands. Even when
isothermal forging is used, shear localization may occur due to flow stress property
[Semiatin et al., 1997].
Metal flow defects such as laps or flow-through defects are more likely to occur in
conventional, closed-die hot forging of difficult-to-work materials. Usually, they can be
avoided by proper die design, well-designed preform, appropriate lubrication and carefully
chosen process variables.
38
In this dissertation, the microstructure characters of titanium alloys, such as volume
fraction of each phase and grain size, are not qualitatively calculated because the
microstructure evolution of titanium alloy in hot deformation is very complex so that it is
not easy to be mathematically described. To authors knowledge, there are no clear-cut
equations used to predict the microstructure of titanium alloys. In this research, distribution
of strain, strain rate, temperature and instability map, which will be introduced in the
following section, will be used to evaluate the forging of titanium alloy.
2.2.3 Related work on forging of titanium alloys
Plenty of research has been done on forging of titanium alloys; some are fundamental
research on material behavior, while others focus on specific parts from industrial
application.
In order to accurately predict the forging process of titanium alloys, it is of great interest to
make deformation behavior well understood. The flow behavior of titanium alloys is
characterized by an initial hardening followed by flow softening (Figure 2.6). Depending
on materials, forming temperature and strain rate, the strain associated with peak stress
may vary a lot.
39
Figure 2.6 Typical stress strain curves for titanium alloys
With the consideration of dynamic recrystallization, viscoplastic constitutive equations
have been employed by Zhou [1998] to model the flow stress of titanium alloy IMI834.
The dynamic recrystallization, which causes the flow softening, was modeled as internal
variables. Material constants were determined by procedure developed by the author.
Experiments carried out at different temperatures and strain rates indicated that the model
can predict the flow stress successfully in isothermal forging conditions.
Besides the use of stress-strain curves, another approach to model constitutive behavior is
processing maps. It is based on principles of dynamic materials model, in which, the metal
being hot worked is assumed to be a nonlinear dissipater of power [Prasad and
Seshacharyulu, 1998]. The energy is dissipated through temperature rise and
microstructural change. How the input power is partitioned between the two is decided by
strain rate sensitivity of flow stress m. The efficiency of power dissipation through
microstructual process is defined as:
40
21
m
m =
+ (2.8)
The efficiency of power dissipation represents the constitutive response of the metal under
various microstructural mechanisms. The power dissipation map, which is constituted by
variation of with temperature and strain rate, can be directly correlated with specific
microstructural mechanisms such as dynamic recrystallization, dynamic recovery, and
wedge cracking.
A continuum instability criterion is used to identify the regimes of flow instabilities. The
instability parameter is defined as:
ln( / 1)( )ln
m mm
+= +
&
& (2.9)
Flow instability is predicted when )( & becomes negative. Thus, the instability map can
be superimposed on the power dissipation map to give a flow instability zone. This map is
called processing map because it can guide process design to optimize workability.
Using power dissipation map and processing map, influences of oxygen content and
starting microstructure on hot deformation of commercial pure titanium, ELI Ti-6Al-4V
and IMI 685 were studied [Prasad and Seshacharyulu, 1998]. The authors concluded that
wide instability regimes existed due to adiabatic shear bands formation at higher strain
rates; the processing of titanium materials is very sensitive to oxygen content and starting
microstructure.
41
The same method was taken by Sechacharyulu et al. [2000] to investigate high oxygen
grade Ti-6Al-4V with equiaxed - microstructure. Material was tested by compression
tests at strain rates of 0.0003, 0.001, 0.01, 0.1, 1, 10 and 100 s-1 and temperature range of
750-1100C at an interval of 50C. The flow stress values were given in great detail and
power dissipation efficiency map and instability map were developed based on these
values (Figure 2.7). The microstructures of compressed samples were examined and the
correlations between the microstructure and maps were explained. The same material with
lamellar starting structure had a different behavior [Seshacharyulu et al., 2002].
Figure 2.7 Power dissipation efficiency map and instability map obtained on Ti-6Al-4V
[Seshacharyulu et al., 2000]
Similarly, deformation behavior of a alloy Ti-10V-4.5Fe-1.5Al in hot forging was studied
by Balasubrahmanyam et al.[Balasubrahmanyam and Prasad, 2002]. Stress strain curves
42
were recorded at temperature range from 650C to 900C and strain rate of 0.001, 0.01, 0.1,
1, 10 and 100 s-1. Power dissipation efficiency maps and instability maps were plotted for
strain of 0.2 and 0.4, respectively. It is noted that the power dissipation efficiency map did
not change significantly with increase of strain; and the instability map at strain of 0.4 was
almost the same as that at strain of 0.2.
The work done by Park et al. [2002] used compression tests to obtain flow stress curves by
which processing maps can be plotted. The criterion authors used to distinguish instability
is different from that mentioned before. One instability zone, which was predicted at
temperature of 1000C and strain rate of 0.001 s-1, indicated a coarse transformed
structure; a long time exposure at high temperature can cause dynamic grain growth. The
processing maps were implemented into subroutine of DEFORM. A pancake forging was
carried out using numerical simulation to show the successful prediction of instability in
the experiments.
The mechanical behavior of Ti-6Al-4V at high and moderate temperatures was studied by
Majorell and co-workers [Majorell et al., 2002]. In addition to the test conducted in hot
processing temperature range, more tests have been done at temperature between
380-680C to investigate the influence of strain rate on the sharp drop in flow stress usually
observed in low strain rate experiments. The test results were correlated with the evolution
of the microstructure. The authors also proposed a physical-based model and the various
43
deformation mechanisms over the tested range were discussed [Picu and Majorell, 2002].
On the contrary, Bruchi et al. [2004] investigated workability of Ti-6Al-4V at high
temperature and strain rate. Correlations between the microstructure of deformed specimen
and deformation parameters were established. At the tested conditions, increasing
temperature or decreasing strain rate can result in a more homogeneous microstructure.
The research also identified a stable flow zone at a temperature between 940 and 950C
and strain rate less than 15 s-1.
By conducting tests with Ti-6Al-4V of two different grain sizes, Semiatin et al. [1999a]
evaluated the flow response and microstructure evolution in hot working with colony
microstructure. A more quantitative understanding of mechanisms that control flow and
globalization was obtained. With critically controlled heat treatment, samples with almost
the same prior-beta grain size but different alpha platelet thickness enabled Semiatin and
Bieler [2001] to study the influence of thickness on flow behavior.
Martin [1998] studied microstructure of Ti-4.4Al-5Mo-2Cr-1Ni by + forging and
forging with subsequent heat treatments. Both microstructure evolution and mechanical
properties show the similar tendency as other + alloys. The research also covered hot
working of non-conventional titanium aluminide. By studying phase transformation and
microstructure, it was found that forging temperature, degree of deformation and annealing
44
temperature have pronounced effect on fatigue strength of + titanium alloys [Kubiak
and Sieniawski, 1998].
Process design rules for non-isothermal forging of Ti-6Al-4V have been proposed in Lee
and Lins work [1998]. In simulation of non-isothermal forging, since a dramatic
temperature gradient exists, the flow stress was determined by localized linear fitting and
interpolation method. The problem was modeled as a coupled thermal plasticity problem;
Youngs modulus, thermal conductivity and specific heat were modeled as
temperature-dependent functions and interface heat conductivity coefficient was assumed
to be pressure dependent. The final shape was considered as a result of deformation
mechanism based on microstructure evolution and deformation index. By comparing the
numerical results of temperature sensitivity factor and deformation index with forged billet,
the authors could establish relations between these two parameters and deformation
behavior.
In order to obtain reliable interfacial boundary data to increase the accuracy of computer
simulation of hot forging of titanium alloys, experiments in conjunction with
thermal-plastic coupled simulations were adopted by Hu and his colleagues [Hu et al.,
1998]. Ring upset tests were conducted at different temperatures with different lubricants
and temperature changes were recorded. The reverse algorithm was applied to finite
element simulation results to iteratively determine the heat transfer coefficient. The work
45
shows that the coefficient varies with die temperature, strain rate, lubricant and forging
pressure.
A lot of research on manufacturing of titanium components, specifically turbine blades, has
been done. Finite element modeling of titanium aluminide aerofoil forging conducted by
Brooks et al. [1998] incorporates flow stress model into finite element codes to simulate
isothermal forging. The predictions of press load and microstructure were in good
agreement with the experiments. The use of re-meshing in simulations also proved to
improve the quality of the calculation. Hu et al. [1999] determined the evolution of
microstructure in blade hot forging by internal state variables. This was extended to
intermetallic alloys later [Hu and Dean, 2001].
Based on their extensive research on blade forging, Zhan et al. [2004] studied the precision
forming of a complex blade with damper platform. In order to inspect and analyze the
deformation process, 4 cross sections and one longitudinal vertical-section were selected.
By analyzing the metal flow and field variable distribution of these 2D cuttings, the
complicated 3D deformation nature can be understood better.
Form errors of turbine blade due to cooling and die deflection caused by loading and
unloading have been investigated by Lu and Balendra [2001]. Results indicated that
forging temperature conditions have a significant influence on die and workpiece behavior.
46
A die shape compensation approach was introduced by Ou and Armstrong [2002] to reduce
the thickn
Top Related