Republic of Iraq Ministry of Higher Education and Scientific Research University of Technology Mechanical Engineering Department

EXPERIMENTAL AND MODELING STUDY ON THE INFLUENCE OF ELECTRICAL DISCHARGE MACHINING PARAMETERS ON THE SURFACE RESIDUAL STRESSES AND FATIGUE LIFE OF DIE STEEL

A Thesis Submitted to the Mechanical Engineering Department of the University of Technology in a Partial Fulfillment of the Requirements for the Degree of Ph.D. in Mechanical Engineering Sciences

By Saad Mahmood Ali (M.Sc. 1994)

Supervised by Asst. Prof. Dr. Ahmed N. AL-Khazraji Asst. Prof. Dr. Samir A. Amin JUNE 2015

Modeling the influence of EDM parameters on the process performances

Dedication To My Father and Mother, My Wife, My Daughters and Sons Shurooq, Ali, Noor, Mohammed with Love

Thanks for endless love, support and encouragement

Saad Mahmood Ali June 2015 |Page2


ACKNOWLEDGMENTS First of all I praise be to ALLAH Almighty for all the blessings without which I could not have completed this work and led me to be mechanical assist lecturer. I would like to express my deepest gratitude and appreciation to my thesis supervisors; Asst. Prof. Dr. Ahmed N. Al-Khazraji and Asst. Prof. Dr. Samir A. Amin for their patience guidance and encouragement throughout this work. Thanks are due to the head of the Mechanical Engineering Department at the University of Technology Asst. Prof. Dr. Moayed Razoki Hasan. Special thanks to the Scientific Deputy Asst. Prof. Dr. Qasim Abbas Atiyah for his help and advices and to all lecturers and associates in the department for all help they have provided. Many thanks are due to the Ministry of Science and Technology and the heads of Department of Technical Affairs and associates for all help they have provided, especially Mr. Khalil Ibrahim and engineer Bashir Riyadh for their efforts while working on electrical discharge machine. Thanks to Department of Engineering Industries in the Central Agency for Standardization and Quality Control for their efforts while working on fatigue testing machine examination. Thanks to the Engineering Inspection Department at the National Center for Laboratories and Research of Construction for their efforts during the X-ray diffraction examinations. Finally, I would like to express my gratitude to my family, my wife, my sons Ali and Mohammed, my daughters Shurooq and Noor for their help and encouragement. Saad Mahmood Ali June 2015 |Page3


ABSTRACT The present work is concerned with studying the effect of electrical discharge machining (EDM) and powder mixing electrical discharge machining (PMEDM) parameters (pulse current, pulse on time,) using copper and graphite electrodes on the output response performance characteristics. These responses were the induced surface residual stresses, the material removal rate (MMR), the tool wear ratio (TWR), the workpiece surface roughness (SR), the white layer thickness (WLT), the total heat flux generated, the workpiece fatigue life and safety factors. Response surface methodology (RSM) and the design of experiment (DOE) were used to plan and design the experimental work matrices for four groups of experiments, two EDM groups using kerosene dielectric alone, where the second was treated by the shot blast peening processes after EDM machining. The third and fourth groups were done by adding the SiC or graphite micro powders mixing to dielectric fluid (PMEDM). To verify the experimental results, the analyses of variance (ANOVA) were used to predict the EDM and PMEDM performance models for high carbon high chromium AISI D2 die steel in terms of empirical equations. The total heat flux generated, the workpiece fatigue life in terms of safety factors after EDM and PMEDM models were developed by FEM using ANSYS 15.0 software. The results showed that the copper electrodes induce lower tensile surface residual stresses by (15.38%) than when using the graphite electrodes with the kerosene dielectric alone, by (7.51%) and (40.0%) with SiC and graphite powders, respectively and by (33%) with shot blast peening processes. Using the copper electrodes and graphite powder |Page4


reduced the induced tensile residual stresses by (79.3%) and (82.6 %) when compared with using kerosene dielectric alone or with SiC powder, respectively. When the graphite electrodes were used with graphite powder, the MRR was improved by (174%) with respect to the value obtained when using copper electrodes with kerosene dielectric alone. The best results of (TWR) were obtained when using the graphite electrodes and kerosene dielectric alone reached (0.1023 %). This result improved the TWR by (320%) with respect to the corresponding value obtained when using copper electrodes with kerosene dielectric alone. The best result obtained when using the graphite electrodes and graphite mixing powder, which improved the SR by (41%) and (92%) compared with using copper electrodes with kerosene dielectric alone and SiC powder, respectively. Using the copper electrodes and shot blast peening after EDM improved the SR when using longer shot peening time (60 min.) by (60.24%) compared with using copper electrodes without shot peening treatments. The copper and graphite electrodes and the SiC powder improved the SR by (134%) and (110%), respectively compared with the using of the same electrodes and kerosene dielectric alone. The WLT reaches its minimum values as (8.34 µm) when using graphite electrodes, where this means an improvement by (40.0 %) when comparing with the using of copper electrodes. The lowest WLT values of (5.0 µm) and (5.57 µm) using the copper and graphite electrodes and the SiC powder, respectivelly. This means an improvement by (134%) and |Page5


(67%) when compared with the using of the copper and graphite electrodes and kerosene dielectric alone, respectively The graphite electrodes gave a higher total heat flux than copper electrodes by (82.4 %) when using kerosene dielectric alone. While, using the SiC powder and graphite electrodes gave a higher total heat flux than copper electrodes by (91.5 %) and by (285.3 %) and (602.7 %) than using the copper and graphite electrodes and the kerosene dielectric alone, respectively. The fatigue life in terms of experimental safety factor with respect to as received material using graphite electrodes after EDM and shot blast peening increased with increasing the shot peening time by (19.10%) and (23.26%) compared with results without using the shot blast peening when using the copper and graphite electrodes, respectively. The graphite electrodes with shot peening processes improved fatigue stresses at (106 cycles) by (19.58 %) and (23.71 %) compared with the copper and graphite electrodes without shot peening processes, respectively. The graphite electrodes with PMEDM and SiC powder improved the experimental fatigue safety factor by (7.30 %) compared with the use of copper electrodes and by (14.61%) and (18.61%) compared with results using the kerosene dielectric alone with copper and graphite electrodes, respectively. The copper electrodes with graphite powder improved the experimental fatigue safety factor by (30.38 %) compared with the using of graphite electrodes and by (15.73 %) and (19.77 %) compared with results of group (2) using the copper and graphite electrodes, respectively.

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The copper electrodes with graphite powder improved the fatigue stresses at (106 cycles) by (26.36 %) compared with the using of graphite electrodes and gave a higher fatigue life than the situation when working without mixing powder by (15.83 %) and (19.83 %) using the copper and graphite electrodes, respectively. Finally, there is a good agreement between the experimental results and the corresponding values verified by using the optimization process for all cases regarding the input parameters of the EDM and PMEDM processes, and this proves the accuracy of the models developed by the RSM and FEM using ANSYS software.

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Table of Contents Acknowledgements

I

Abstract

II

Table of Contents

V

List of Tables

XII

List of Figures

XIV

Nomenclature

XX

List of Abbreviations

XXIII

Chapter 1: INTRODUCTION 1.1 Overview

1

1.2 The Sinker Type Electrical Discharge Machine

2

1.3 EDM Working Principle Mechanism

4

1.4 Advantages and Disadvantages of EDM Processes

5

1.5 The Workpiece Material

6

1.6 The Electrodes Materials

7

1.7 Powder Additives to Dielectric Fluid

7

1.8 The Surface Residual Stresses

8

1.9 The Shot Blast Peening Treatment

9

1.10 The EDM Workpiece Fatigue Properties

9

1.11 Modeling of EDM Processes

10

1.12 The Research Problems

10

1.13 The Objectives of This Work

11

Chapter 2: LITERATURE REVIEW |Page8


2.1 Previous Works on EDM Performances Related with SR, MRR

13

and TWR 2.2 Previous Works on Powder mixed EDM (PMEDM)

16

2.3 Previous Works on Surface Residual Stresses and Fatigue

18

Strength for EDM 2.7 Concluding Remarks

25

2.8 The Role of Present Work

26

Chapter 3: NUMERICAL ANALYSIS 3.1 Introduction.

28

3.2 Theory and Formulation

28

3.3 Thermal Modeling of EDM and PMEDM Processes

29

3.3.1 The governing equation

30

3.3.2 The heat flux due to a single spark

30

3.3.3 Boundary conditions

31

3.3.4 The heat flux in EDM and PMEDM

33

3.3.5 Energy partition (Rw) due to EDM between cathode,

35

anode and dielectric liquid 3.3.6 Discharge channel radius and profile

35

3.3.7. The latent heat

36

3.3.8. Spark frequency and breakdown voltage

37

3.3.9. Thermal stress distribution

38

|Page9


3.4 Surface Residual Stress Distribution

39

3.5 Modeling and Simulation of the Total Heat Power in EDM and

39

PMEDM Processes by Using FEM 3.5.1 Introduction

39

3.5.2 Applications of FEM to thermal modeling of EDM and

40

PMEDM processes 3.5.3 The thermal models boundary conditions

42

3.5.4 Materials properties

43

3.5.5 Simulation of the thermal models

43

3.5.6 The procedure steps used for thermal modeling of EDM

45

and PMEDM processes 3.6 Modeling and Simulation of the Fatigue Life in EDM and

47

PMEDM Processes by Using FEM 3.6.1. Simulation of the fatigue life models

49

3.6.2 The main procedure steps used for fatigue life modeling

50

of EDM and PMEDM processes Chapter 4: EXPERIMENTAL WORK 4.1 Fabricating and Testing the Workpiece Material

52

4.2 Fabricating the Workpiece Specimens

55

4.3 The Surface Roughness Measurement of Workpieces and

56

Electrodes 4.4 Measuring the Surface Residual Stresses of Workpieces

56

| P a g e 10


Materials 4.5 Fabricating the Copper and Graphite Electrodes

58

4.5.1 The weighing of workpieces and electrodes

58

4.5.2 Fabricating the electrodes spindle holder

59

4.6 Design and Fabricating the Powder Mixed (PMEDM) Device

60

4.7 Selecting and Preparing the EDM Parameters

61

4.8 Testing the Kerosene Dielectric and Powders Materials

62

4.9 Implementation the Designed EDM and PMEDM Experiments

62

4.9.1 Initial experiments for testing the possibilities of EDM

63

machine 4.9.2 Implementation the main EDM and PMEDM

65

experiments 4.9.2.1 EDM group (1) experiments using kerosene

66

dielectric alone 4.9.2.2 EDM group (2) experiments and laser or shot

67

blast peening treatments 4.9.2.3 PMEDM experimental group (3) using Silicon

69

Carbide powder 4.9.2.4 EDM experimental group (4) using graphite

70

powder mixing PMEDM 4.10 Experimental and Testing Works after EDM and PMEDM

72

| P a g e 11


Machining 4.10.1 The weighing process

73

4.10.2 The shot blast peening surface treatment for group (2)

73

after EDM machining 4.10.3 The hardness measurements after EDM, PMEDM and

74

after blast shot peening processes 4.10.4 The measurements of surface roughness (SR) after

75

EDM and PMEDM machining and after shot blast peening processes 4.10.5 The measurements of surface residual stresses after

75

EDM and PMEDM machining and after shot blast peening processes 4.10.6 Examination of surface recast white layers micro

75

defects using the optical microscope (OM) 4.10.7 Estimating and calculating the surface integrity

76

indication parameters 4.10.7.1 Estimating and calculating the material removal

76

rate (MRR) 4.10.7.2 Calculation the tool wear ratio (TWR)

77

4.10.8 Estimating and calculating the fatigue life

77

4.10.8.1The establishing of S/N curve for as received

78

AISI D2 die steel

| P a g e 12


4.10.8.2 Estimating and calculating the fatigue life for

79

all the EDM, PMEDM and shot blast peening experimental groups Chapter 5: RESULTS AND DISCUSSIONS 5.1. The Workpiece and Other Used Materials Testing Results

81

5.2. Initial Experimental Results of Testing the EDM Machine

83

Possibilities 5.3.

Modelling the Surface Residual Stresses Induced by EDM

83

and PMEDM Machining 5.3.1 Design of experiments (DOE)

84

5.3.2. The analysis of variance (ANOVA) technique

87

5.3.3 The surface residual stresses results

89

5.3.5. Numerical optimization

98

5.4. Prediction Models of Surface Roughness, Material Removal

101

Rate and Tool Wear Ratio for All EDM and PMEDM Experimental Groups 5.4.1 Prediction models of material removal rate (MRR) for

102

all EDM and PMEDM experimental groups 5.4.1.1. Numerical optimization of material removal

108

rate (MRR) results 5.4.2. Predicted models of tool wear ratio (TWR) for all EDM

109

and PMEDM experimental groups 5.4.2.1. Numerical optimization of tool wear ratio

115

| P a g e 13


(TWR) results 5.4.3. Predicted models of surface roughness (SR) for all

115

EDM and PMEDM experimental groups 5.4.3.1. Numerical optimization of surface roughness

126

(SR) results 5.5. The Rockwell Hardness Tests for all Experimental groups

127

5.6. Calculation of the White Layer Thickness (WLT) for All

134

Experimental Groups 5.7. FEM Solution and Analysis of EDM and PMEDM Processes

147

by Using ANSYS Software 5.7.1 FEM solutions of thermal models for EDM and

147

PMEDM processes 5.7.2. FEM Solutions of thermal models for all experimental

155

groups 5.8. FEM Solutions of Fatigue Life for All EDM and PMEDM

164

Experimental Groups 5.8.1. FEM solutions for establishing the S/N fatigue curve

165

models for as received die steel material / group (5) Experiments 5.8.2. FEM solutions for determining fatigue life and safety

169

factor models for all experiments groups Chapter 6: CONCLUSIONS AND RECOMMENDATIONS | P a g e 14


6.1. Conclusions

233

6.1.1. Conclusions related to the surface residual stresses results

233

6.1.2. Conclusions related to the material removal rate (MRR),

234

tool wear ratio (TWR) and the surface roughness (SR) results 6.1.3. Conclusions related to the Rockwell hardness tests results

235

6.1.4. Conclusions related to White Layer Thickness (WLT)

235

results 6.1.5. Conclusions related to total heat flux generated results

236

6.1.6. Conclusions related to fatigue safety factor and fatigue

237

lives results 6.2. Recommendations

239

References Published papers Appendix (I)

| P a g e 15


List of Figures Figure No. Figure 1.1 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 Figure 3.5 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 4.5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Figure 4.10 Figure 4.11 Figure 4.12 Figure 4.13 Figure 4.14 Figure 4.15 Figure 4.16 Figure 4.17 Figure 4.18 Figure 4.19 Figure 4.20 Figure 4.21

Legend Page The sinker type EDM Schematic diagram 3 Schematic sketch of Gaussian heat distribution for 30 the thermal model in EDM and PMEDM process The thermal model for EDM and PMEDM 31 processes The Gaussian distribution 33 The spark frequency in: (a) EDM, (b) PMEDM 38 The Goodman mean stress correction theory 49 The raw material strips used in the present work 53 The material analyzer type “Ametex Spectro 53 The finished mechanical properties test specimens 54 before testing The mechanical test specimen 54 The optical microscope (OM) set 55 The specimens' dimensions and shape for fatigue 55 tests The Avery Denison plain bending fatigue testing 56 machine type 7305, capacity 30 N.m, England The all fabricated workpiece specimens 56 The Portable surface roughness tester 57 The XRD test apparatus type Shimadsu /Japan 57 Fabricated the copper electrodes raw materials 58 The weighing process for the workpieces 59 specimens by using the electronic balance The weighing process for the fabricated electrodes 59 The fabricated electrodes holder 60 The fabricated stainless steel container with all 60 accessories The Laser Diffraction Particle size Analyzer 63 The ACRA CNC-EB series EDM machine 63 The copper electrode used in the initial 64 experiments The X-MET 3000TX HORIZONT metal analyzer 64 The (CNC) EDM machine with all the fabricated 66 accessories The workpieces prepared for group (1) EDM 67 experiments | P a g e 16


Figure 4.22 Figure 4.23 Figure 4.24 Figure 4.25 Figure 4.26 Figure 4.27 Figure 4.28 Figure 4.29 Figure 4.30 Figure 4.31 Figure 4.32 Figure 4.33 Figure 5.1 Figure 5.2 Figure 5.3

Figure 5.4

Figure 5.5 Figure 5.6

The specimens and the used copper and graphite electrodes for group (1) experiments after EDM The workpieces prepared for group (2) EDM experiments The specimens and the used copper and graphite electrodes for group (2) experiments after EDM The workpieces prepared for group (3) PMEDM experiments The specimens and the used copper and graphite electrodes for group (3) experiments after PMEDM machining The assemblies and attachments manufactured for doing the powder mixing PMEDM experiments The mixed dielectric fluid flashing from both sides of the electrode-workpiece interface gap The workpieces prepared for group (4) PMEDM experiments The specimens and the used electrodes for group (4) experiments after PMEDM machining The drum type blast wheel (impeller) shot blasting machine with a fabricated specimen's fixture The selected specimens representing all EDM and PMEDM parameters prepared for WLT and surface topography tests The fatigue test specimens for establishing the S/N curve for the tested material The graph columns for experimental group (1) The normal probability plot the residuals for copper electrodes The normal probability plot the residuals, for graphite electrodes The 3D graph models graphs for the effect of EDM and PMEDM parameters on surface residual stresses for all experimental groups using copper electrodes The 3D graph models graphs for the effect of EDM and PMEDM parameters on surface residual stresses for all experimental groups using graphite electrodes The bar graphs with a maximum desirability ratio

68 68 69 69 70 71 71 72 72 74 76 80 86 90 90

92

94 100

| P a g e 17


Figure 5.7

Figure 5.8

Figure 5.9

Figure 5.10

Figure 5.11

Figure 5.12

Figure 5.13

Figure 5.14

Figure 5.15

Figure 5.16

Figure 5.17 Figure 5.18 Figure 5.19 Figure 5.20

of the predicted surface residual stresses for copper electrodes The bar graphs with a maximum desirability ratio of the predicted surface residual stresses for graphite electrodes The 3D graph models for the effect of EDM and PMEDM parameters on MRR for all experimental groups using copper electrodes The 3D graph models for the effect of EDM and PMEDM parameters on MRR for all experimental groups using graphite electrodes The 3D graph models for the effect of EDM and PMEDM parameters on TWR for all experimental groups using copper electrodes The 3D graph models for the effect of EDM and PMEDM parameters on TWR for all experimental groups using graphite electrodes The 3D graph models for the effect of EDM and PMEDM parameters on SR for all experimental groups using copper electrodes The 3D graph models for the effect of EDM and PMEDM parameters on SR for all experimental groups using graphite electrodes The 3D graph models for the effect of EDM and shot blast peening processes on SR for group (2) using copper electrodes The 3D graph models for the effect of EDM and blast shot peening parameters on SR for group (2) using graphite electrodes The effect of EDM and PMEDM parameters on Rockwell hardness (HRB) values for all experimental groups using copper electrodes The effect of EDM and PMEDM parameters on Rockwell hardness (HRB) values for all experimental groups using graphite electrodes The WLT for all experimental groups after EDM and PMEDM using copper electrodes The WLT for all experimental groups after EDM and PMEDM using graphite electrodes The axisymmetric three-dimensional geometrical

101

106

107

113

114

120

121

123

124

131

133 139 140 148

| P a g e 18


Figure 5.21 Figure 5.22 Figure 5.23 Figure 5.24 Figure 5.25

Figure 5.26 Figure 5.27 Figure 5.28 Figure 5.29 Figure 5.30 Figure 5.31 Figure 5.32 Figure 5.33 Figure 5.34 Figure 5.35 Figure 5.36 Figure 5.37

model of the problem The axisymmetric three-dimensional geometrical model for the workpiece and the electrode The three-dimensional meshed models for the workpiece, the electrode and the used kerosene dielectric The three-dimensional meshed models for the workpiece and the electrode The setting of the transient thermal models domain loads The total heat flux generated by the EDM and PMEDM machining for all experimental group using copper electrodes The total heat flux generated by the EDM and PMEDM machining for all experimental group using copper electrodes The axisymmetric three-dimensional workpiece geometrical model of the problem The three-dimensional meshed models for the workpiece The three-dimensional meshed models for the flat workpiece Setting of the fixing supported and the loading force sides The semi-log S/N curve for the as received workpiece material fatigue testing results The fatigue life model simulations for flat die steel specimens fatigue life The model simulations for flat die steel specimens fatigue factor of safety The model simulations for fatigue strength factor for the flat after EDM and PMEDM machining specimens The S/N curves for experimental sub-groups (1), using pulse current (8 A) The S/N curves for experimental sub-groups (1), using pulse current (22 A) The fatigue safety factor for all experimental groups after EDM and PMEDM using copper electrodes

149 149 150 150 162

163 166 167 167 168 169 170 171 171 179 179 183

| P a g e 19


Figure 5.38

Figure 5.39

Figure 5.40

Figure 5.41

Figure 5.42

Figure 5.43

Figure 5.44

Figure 5.45

Figure 5.46

The fatigue safety factor for all experimental groups after EDM and PMEDM using graphite electrodes The fatigue stresses at (106cycles) for all experimental groups after EDM and PMEDM using copper electrodes The fatigue stresses at (106cycles) for all experimental groups after EDM and PMEDM using graphite electrodes The S/N curves for experimental sub-groups (2) after EDM and shot peening, using pulse current (8A) The S/N curves for experimental sub-groups (2)after EDM and shot peening, using pulse current (22A) The S/N curves for experimental sub-groups (3) after PMEDM using the SiC powder mixing and pulse current (8A) The S/N curves for experimental sub-groups (3) after PMEDM using the SiC powder mixing and pulse current (22A) The S/N curves for experimental sub-groups (4) after PMEDM using the graphite powder mixing and pulse current (8A) The S/N curves for experimental sub-groups (4) after PMEDM using the graphite powder mixing and pulse current (22A)

185

188

190

191

191

193

194

196

196

| P a g e 20


List of Tables Table No.

Legend Page The mechanical and thermal properties of workpiece, Table 3.1 44 electrodes, powders mixing and kerosene dielectric The chemical compositions for the selected Table 5.1 workpiece material and the equivalent given by the 81 standard for AISI D2 die steel Table 5.2 The mechanical properties for the selected materials 82 The chemical compositions of the selected copper Table 5.3 82 electrode material The EDM machining experimental parameters for Table 5.4 83 initial testing of machine The surface residual stresses designed experimental Table 5.5 matrix for all experimental groups using the copper 85 electrodes The surface residual stresses designed experimental Table 5.6 matrix for all experimental groups using the graphite 85 electrodes The (ANOVA) analyses for the EDM subgroup (1) Table 5.7 87 experiments using copper electrodes The (ANOVA) analysis for the EDM subgroup (2) Table 5.8 88 experiments using graphite electrodes The new constraints goals for numerical optimization Table 5.9 99 for copper electrodes The desirability process for optimization of the Table 5.10 predicted surface residual stresses for copper 100 electrodes The desirability process for optimization of the Table 5.11 predicted surface residual stresses for graphite 100 electrodes The design experimental matrix for MRR for all EDM and PMEDM machining experimental groups The design experimental matrix for TWR for all Table 5.13 EDM and PMEDM machining experimental groups The design experimental matrix for SR for all EDM Table 5.14 and PMEDM machining experimental groups The designed experimental matrix for SR group (3) Table 5.15 after EDM and shot blast peening processes Table 5.12

102 109 116 116 | P a g e 21


Table 5.16 Table 5.17 Table 5.18 Table 5.19 Table 5.20 Table 5.21 Table 5.22

Table 5.23

Table 5.24 Table 5.25

Table 5.26

Table 5.27

Table 5.28 Table 5.29 Table 5.30

Table 5.31

The average values of workpieces surface Rockwell hardness tests (HRB) for all experimental groups Calculation the average values of the white layer thickness (WLT) for all experimental groups after EDM and PMEDM machining The white layer thickness (WLT) microstructures for EDM groups (1and 2) using kerosene dielectric The WLT microstructures for PMEDM group (3) using kerosene dielectric and SiC mixed powder The WLT microstructures for PMEDM group (4) using kerosene dielectric and graphite mixed powder Experimentally estimated values of (Kn) factor for all EDM and PMEDM machining groups The total heat flux (power) fraction values absorbed by the workpieces for all EDM and PMEDM machining groups The heat flux (power) fraction values absorbed by the electrode for all EDM and PMEDM machining groups The heat flux (power) fraction values absorbed by the kerosene dielectric for all EDM and PMEDM machining groups The experimental and numerical total heat flux (power) generated by EDM processes for groups (1 and 2), using kerosene dielectric The experimental and numerical total heat flux (power) generated by PMEDM processes using kerosene dielectric with SiC mixed powder The experimental and numerical total heat flux (power) generated by PMEDM processes using kerosene dielectric with SiC mixed powder The experimental heat flux (power) generated by EDM (group 1) and PMEDM (group 3) processes The experimental heat flux (power) generated by EDM (group 1) and PMEDM (group 4) processes The total modeled heat flux generated by the EDM group (1 and 2) experiments using pulse current (22 A) and pulse on time (40 µs) The total modeled heat flux generated by the PMEDM experiments using the SiC mixed powder,

128 135 141 143 145 152 153

153

154

156

156

157 157 157 159 160 | P a g e 22


Table 5.32

Table 5.33 Table 5.34

Table 5.35

Table 5.36

Table 5.37

Table 5.38 Table 5.39 Table 5.40 Table 5.41

Table 5.42

Table 5.42

the pulse current (22 A) and pulse on time (40 µs) The total modeled heat flux generated by the PMEDM experiments using the graphite mixed powder, the pulse current (22 A) and pulse on time (40 µs) Experiment group (5) for establishing the S/N fatigue curve for AISI D2 die steel The experimental average values of fatigue stress at (106 cycles) and fatigue safety factor for group (1) using kerosene dielectric The experimental average values of fatigue stress at (106 cycles) and fatigue safety factor for group (2) after EDM and shot blast peening processes The experimental average values of fatigue stress at (106 cycles) and fatigue safety factor for group (3) PMEDM machining with SiC powder mixing The experimental average values of fatigue stress at (106 cycles) and fatigue safety factor for group (4) PMEDM machining with graphite powder mixing The experimental values of fatigue stress at (106 cycles) for EDM group (1) and PMEDM group (3) The experimental values of fatigue stress at (106 cycles) for EDM group (1) and PMEDM group (4) The FEM fatigue life and safety factor Models for group (1), using the copper and graphite electrodes The FEM fatigue life and safety factor Models for group (2) after EDM machining and shot blast peening processes The FEM fatigue life and safety factor Models for PMEDM machining of group (3) with SiC powder mixing The FEM fatigue life and safety factor Models for PMEDM machining of group (4) with graphite powder mixing

161

168 172

172

173

173 173 174 175 176

177

178

| P a g e 23


Nomenclature English Symbols Symbols b

Cm

Meaning

Units mm

Specific heat capacity of workpiece material in

J/Kg K

Specimen width

melting state

Cp E

Specific heat capacity of workpiece material in solid state Young’s modulus

J/Kg K

h

specimen thickness

hf Ip

Heat transfer coefficient between the workpiece surface and dielectric The Pulse Current

𝒌

Thermal conductivity of the material

Kf

Fatigue strength factor

Kn 𝑳𝒎

Parameter of the effect of suspended powder particles Latent heat due to melting

KJ/Kg

𝑳𝒆𝒗

Latent heat due to evaporation

KJ/Kg

GN/m2 mm

A J/m K s

M

Moment

N.m

M1

The mass of the workpiece before EDM

gm

M2

The mass of the workpiece after EDM

gm

ME

The mass of the tool (electrode)

gm

MW

The mass of the workpiece

gm

Nf P

Number of cycles to failure

Cycle

Power

KVA

𝑷(𝒓)

Q0

The intensity of heat imparted to the workpiece surface The maximum intensity of heat applied at the axis of a spark | P a g e 24


𝑸𝒘(𝒓) R Ra

Rw

Heat flux entering the workpiece during the pulse on-time Stress ratio

MW/m²

Average surface roughness

μm

The energy percentage fraction of heat input to

%

the workpiece R, r

Spark radius

µm

R(t)

Heat input spark radius

µm Mm3

S

Section modulus

SN

The total number of discharge sparks

𝒕

Time

𝑻

Temperature

T

Machining time

𝑻𝟎

Initial temperature

K

Tm Ton

Melting temperature The Pulse on Time Period

K µs

TOff

The Pulse off Time Period

µs

Tt

Melting point of the tool electrode

°C

Tw

Melting point of the workpiece material

°C

V

Voltage

V

Vb

The breakdown voltage

V

VE

Volume of material removal from the electrode

VW

Volume of material removal from the workpiece

Vp

The Gap Voltage

min. K min.

mm3

V

Greek Symbols Symbols 𝝂

ρ

Description Poisson's ratio Density

Units Kg/m3 | P a g e 25


ρE ρw η

𝝈 𝝈b Δσ σu 𝛅

Density of the electrode material

gm/mm³

Density of the workpiece material The Duty Factor

gm/mm³ %

Stress Fatigue stress at (106 cycles) Cyclic stress range Ultimate tensile strength The standard deviation

N/m2 N/m2 N/m2 N/m2 %

| P a g e 26


List of Abbreviations Symbol AFM AISI ANOVA APC APS BHN CCD CNC CNT 3D DC ED EDA EDM EWR FFD FE FEA FEM HAZ HRB HCF HSC HSS LP MRR OM OSM pdf PM PMEDM P.P. PVD RPM RSM RWR

Meaning Units Atomic Force Microscope American Iron and Steel Institute Analysis of Variance Abrasive Particle Concentration % Abrasive Particle Size Brinell Hardness Number N/mm² Central Composite Design Computer Numeric Controlled Carbon Nano Tube Three Dimensional Direct Current A Electrical Discharge Electrical Discharge Alloying Electrical Discharge Machining (Machine) Electrode Wear Ratio % Full Factorial Designs Finite Element Finite Element Analysis Finite Element Method Heat Affected Zone Hardness Rockwell Ball High Cycle Fatigue Cycles High Speed Cutting High Speed Steel Laser Peening Material removal rate of workpiece mm3/min Optical Microscope Optical stereo microscope Probability density function of Gaussian distribution Powder Metallurgy Powder Mixing Electrical Discharge Machining Jump of electrode Physical Vapor Deposition Revolution PER minute Response Surface Methodology Relative Wear Ratio % | P a g e 27


S SEM SR S.V. TIG TWR UTS XRD WEDM WLT W/P

Section modulus Scanning Electron Microscope Surface Roughness Servo gap sensitivity (Servo) Tungsten Inert Gas Tool Wear Ratio Ultimate Tensile Strength X-Ray Diffraction Wire Electrical Discharge Machining (Machine) White layer thickness Workpiece

mm³ µm

% MPa

µm

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Chapter

1

INTRODUCTION 1.1 Overview The erosive effect of electrical discharges or sparks was first noted in 1770 by English physicist and chemist Joseph Priestley. However, it was only in 1943 at the Moscow University where two Russian scientists, B. R. Lazarenko and N. I. Lazarenko exploited the destructive properties of electrical discharges for constructive use. They developed a controlled process of machining difficult-to-machine metals by vaporizing material from the surface of metal. The first CNC Electrical discharge machine (EDM) was produced in 1976. It was only in the 1980s with the advent of computer numerical control (CNC) in EDM, which implied an automatic and unattended machining from inserting the electrodes in the tool changer to finished polished cavities [1]. EDM is a non-traditional manufacturing process whereby a desired shape is obtained using electrical discharges (sparks) [2]. Material is removed from the workpiece by a series of rapidly recurring current discharges between two electrodes, separated by a dielectric liquid and subjected to an electric voltage. One of the electrodes is called the toolelectrode, or simply the ‘tool’ or ‘electrode’, while the other is called the workpiece-electrode, or ‘workpiece’. At present, EDM is a widespread technique used in industry for high-precision machining of all types of conductive materials, hard and difficult-to-machine, such as heat treated tool steels, titanium, super alloys, | P a g e 29


hastalloy, inconel, carbides, stainless steels, heat resistant steel, graphite or even some ceramic materials of any hardness, polycrystalline diamond tools, etc. [3]. EDM machining technique has been accepted worldwide as a standard process in manufacturing areas as: dies and molds making industries. It has also made a significant inroad in the new fields, such as sports, medical, surgical instruments, biomedical applications, optical, dental and jewelry industries, and in automotive, aircraft, aerospace applications, aeronautics, micromechanics, nuclear, microelectronic and other industries [4]. EDM process is now becoming a common method of making prototype and production parts, especially in the aerospace, automobile and electronics industries. Micro-EDM is capable of machining not only microholes and micro-shafts as small as 5 μm in diameter, but also complex three dimensional (3D) micro cavities. 1.2 The Sinker Type Electrical Discharge Machine Sinker EDM, consists of conducting electrode and workpiece submerged in an insulating liquid, such as, more typically, oil or, less frequently, other dielectric fluids, like kerosene or deionized water [5]. The sinker type EDM schematic diagram is shown in figure (1-1). The electrode and workpiece are connected to a suitable DC power supply. Generally, the tool is connected to the negative terminal (cathode) of the generator, and the workpiece is connected to positive terminal (anode). The power supply generates an electrical potential at the gap between the tool and workpiece, which depends upon the applied potential difference (50 to 450 V), and an electric field would be established. The current density in the discharge of the channel is of the order of 10000 | P a g e 30


A/cm², and the power density is nearly 500 MW/cm². As the electrode approaches the workpiece, the dielectric breakdown occurs in the fluid, forming a plasma channel, and a small spark (known as spark gap) jumps through a gap in the range, from 0.005 mm to 0.05 mm [6].

Figure (1-1): The sinker type EDM Schematic diagram [7] These sparks happen in huge numbers at seemingly random locations between the electrode and the workpiece. As the base metal is eroded, and the spark gap is subsequently increased, the electrode is lowered automatically by the machine servo system so that the process can continue uninterrupted. Several hundred thousand sparks occur per second, with the actual duty cycle carefully controlled by the setup parameters. These controlling cycles are sometimes known as "on time" and "off time" [7]. The on time setting determines the duration of the spark. Hence, a longer on time produces a deeper cavity for that spark and all subsequent sparks for that cycle, create an eroded debris and rougher finish on the | P a g e 31


workpiece. The reverse is true for a shorter on time. Off time is the period of time that one spark is replaced by another. A longer off time, for example, allows the flushing of dielectric fluid through a nozzle to clean out the eroded debris, thereby avoiding a short circuit. These settings can be maintained in microseconds. The dielectric pressure is forced through this gap at a pressure of 2 kgf/cm² or less. 1.3 EDM Working Principle Mechanism When the distance between the two electrodes is reduced, the intensity of the electric field in the volume between the electrodes becomes greater than the strength of the dielectric (at least in some points), which breaks, allowing current to flow between the two electrodes. This phenomenon is the same as the breakdown of a capacitor (condenser) (breakdown voltage). As a result, material is removed from both the electrodes. Spark is initiated at the point of smallest inter-electrode gap by a high voltage, overcoming the dielectric breakdown strength of the small gap. At this stage, erosion of both the electrodes takes place, after each discharge. Once the current flow stops, new liquid dielectric is usually conveyed into the inter-electrode volume enabling the solid particles (debris) to be carried away and the insulating properties of the dielectric to be restored. Adding new dielectric liquid in the inter-electrode volume is commonly referred to as flushing. These craters can be of typical dimensions ranging from the nano scale (in micro-EDM operations) to some hundreds of micrometers in roughing conditions. The material erosion mechanism primarily makes use of electrical energy and turns it into thermal energy through a series of discrete electrical discharges occurring between the electrode and workpiece | P a g e 32


immersed in a dielectric fluid. The thermal energy generates a channel of plasma between the cathode and anode at a temperature in the range of 8000 to 12000 °C or as high as 20000 °C, initializing a substantial amount of heating and melting of material at the surface of each pole. When the pulsating direct current supply occurring at the rate of approximately 20.000 – 30.000 Hz is turned off, the plasma channel breaks down [8]. This causes a sudden reduction in the temperature, allowing the circulating dielectric fluid to implore the plasma channel and flush the molten material from the pole surfaces in the form of microscopic debris. EDM is erosion process of melting and evaporating material from the workpiece and electrode surfaces. The first serious attempt of providing a physical explanation of the material removal during electric discharge machining is that of Van Dijck, who presented a thermal model together with a computational simulation to explain the phenomenon between the electrodes during electric discharge machining [9]. However, as Van Dijck himself admitted in his study, the number of assumptions made to overcome the lack of experimental data at that time was quite significant. Further models in terms of heat transfer were developed in the late eighties and early nineties, including an investigation at Texas A&M University. It resulted in three scholarly papers: the first presenting a thermal model of material removal on the cathode [10], the second presenting a thermal model for the erosion occurring on the anode [11] and the third introducing a model describing the plasma channel formed during the passage of the discharge current through the dielectric liquid [12]. Validation of these models is supported by experimental data. These models give the most authoritative support for the claim that EDM is | P a g e 33


a thermal process, removing material from the two electrodes because of melting and/or vaporization, along with pressure dynamics established in the spark-gap by the collapsing of the plasma channel [5]. 1.4 Advantages and Disadvantages of EDM Processes Some of the advantages of EDM are: 1- It is a unique method to machine parts regardless of hardness, since the tool does not touch the workpiece and there are no cutting forces generated. 2- 3D Complex shape part geometries, like thread cutting, helical profile milling, rotary forming, deep narrow slots, curved holes drilling can be produced by EDM that would be difficult to produce with conventional cutting tools [13]. 3- Very small workpieces can be made, because conventional cutting tools may damage the part from the excess cutting tool pressure [14]. 4- Since there is no direct contact between the tool and workpiece and there is no mechanical stress present, fragile and slender work parts can be machined by EDM without any distortion [13]. 5- It has repeatability and is easily automated [15]. Some of the disadvantages of EDM include: 1- The slow rate of material removal. 2- For economic production, the surface finish specified should not be too fine. 3- The additional time and cost are used for creating electrodes for ram/sinker EDM. 4- Excessive tool wear occurs during machining. 5- Undesirable recast layer may need to be removed. 6- Leaves a highly stressed surface layer. | P a g e 34


1.5 The Workpiece Material Die steels are used to construct the die components subject to wear in a variety of presses working operations. These steels are designed specially to develop high hardness levels and abrasion resistance when heat-treated [16]. Die steels used for making tools, punches, and dies are perhaps the hardest, the strongest, and toughest steels used in industry. In general, die steels are basically medium- to high-carbon steels with specific elements included in different amounts to provide special characteristics. AISI D2 tool steel of series D, mainly used for cold working processes, also known as die steels, was selected to be used in this work due to its emergent range of applications in the field of manufacturing tools in mold industries [16-17]. It is equivalent to German DIN 1.2080 (X210 Cr12) and Russian GOST X 12 standards. The AISI D2 die steel is an air hardened, high carbon, and high chromium content steel alloyed with molybdenum that offers the ability to be hardened in air, gives a high degree of dimensional stability in hardening heat treatment, good throughhardening properties, and good resistance to tempering-back. It also contains vanadium characterized by extremely high wear resistance due to formation of vanadium carbide in heat treatment combined with moderate toughness (shock-resistance) and compressive strength, good through-hardening properties and resistance to temperingback. 1.6 The Electrodes Materials The main requirements for electrode materials are: the higher density for less tool wear and dimensional loss or inaccuracy of tool, high melting point for less tool wear due to less tool material melting for the

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same

heat

load,

maximum

possible

metal

removal

rate,

easy

manufacturability and low cost. In this study, two types of cutting tool (electrode) materials are used, i.e., graphite and copper. Graphite has fair wear characteristics, and is easily machinable. Copper has higher density, good EDM wear and better conductivity. 1.7 Powder Additives to Dielectric Fluid EDM process suffers from few limitations, such as low machining efficiency and poor surface finish. To overcome these limitations, a number of efforts have been made to develop such EDM systems without making any major alterations in its basic principle [18]. The techniques used include: (i) electrode rotating, (ii) electrode orbiting-planetary motion to tool or workpiece, (iii) applications of ultrasonic vibrations, and (iv) suspension of foreign powders in the dielectric fluid. The mixing of a suitable abrasive and metallic material in powder form into the dielectric fluid is one of the latest advancement for improving the innovations and enhancement capabilities of EDM process [19]. This process is called powder mixed EDM (PMEDM). In this process, the electrically conductive powder particles are mixed in the dielectric fluid, which reduces its insulating strength and increase the spark gap distance between the tool and workpiece to spread the electric discharge uniformly in all directions. Till now, very few researches have been done in machining operation with addition of powder mixed EDM. A number of fundamental issues of this new development, including the machining mechanism, are still not well understood [20-22].

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1.8 The Surface Residual Stresses Residual stresses in a workpiece are a function of its material processing and machining history. They act in a body without applying forces or moments and changing the level of the yield strength [23]. Electrical discharge machining (EDM) is a thermal erosion process [24]. The instantaneous temperature rise during the machining process changes the physical properties of the machining surface layer, resulting in the presence of residual stress which is one of the key factors affecting the machined surface quality and its functional performance. Residual stresses generated during EDM are mainly due to the nonhomogeneity of heat flow and metallurgical transformations or to localized inhomogeneous plastic deformation. In EDM process, the change in surface quality is directly related to the amount of energy used for removing material from the surface. Investigation of the residual stresses of EDM machined components revealed their tensile nature, thermal residual stresses are created on the upper layer of workpiece surface due to rapid solidification of EDM processes, which will influence the component properties. The X-ray method is one of the non-destructive techniques for the measurement of residual stresses on the surface of materials. X-ray diffraction techniques exploit the fact that when a metal is under stress, applied or residual stress, the resulting elastic strains cause the atomic planes in the metallic crystal structure to change their spacing, then the total stress on the metal can be obtained [25]. 1.9 The Shot Blast Peening Treatment Shot blast peening uses smooth hard steel balls shot at high veloci| P a g e 37


ties to yield a plastic deformation on the workpiece surface layer. During the shot peening process, each piece of shot that strikes the material acts as a tiny peening hammer, causing to the surface a small indentation or dimple. Shot peening is the most economical and practical method of ensuring surface residual compressive stresses. Compressive stresses are beneficial in increasing the fatigue strength, the wear resistance, endurance limit, corrosion fatigue and to obtain better surface hardness and quality. Shot peening significantly improves the poor fatigue performance after EDM [26-27]. 1.10 The EDM Workpiece Fatigue Properties EDM components are commonly applied at high temperature, highstress, and high-fatigue-load environments. Under such conditions, the cracks on the machined surface act as stress raisers and lead to a considerable reduction in the fatigue life of the component. Researchers have proposed improving the fatigue life of EDM component by using a post-machining operation to remove the recast layer or to coat the machined surface with a metallic layer. However, both methods inevitably extend the manufacturing time and increase the manufacturing cost. Accordingly, the current study conducts an experimental investigation of two methods (the powder mixing that does not need post-treatment processing and the economic and quick shot blast peening process) to identify the optimal EDM machining parameters which suppress the formation of cracks in the recast layer for longest lives under different fatigue loads [28]. 1.11 Modeling of EDM Processes Many attempts have been made for modeling of EDM process, and | P a g e 38


investigations on the process performance are still challenging problems. Due to the complexity in nature, there is a lack of analytical models correlating the process variables, which restrict the expanded application of the technology [29]. EDM process is very demanding but the mechanism of process is complex and far from being completely understood. Therefore, it is hard to establish a model that can accurately predict the response (productivity, surface quality, etc.) by correlating the process parameter, though several attempts have been made [30]. Since it is a very costly process, optimal setting of the process parameters is the most important to reduce the machining time to enhance the productivity [22]. Improving the MRR and surface quality are still challenging problems that restrict the expanded application of the technology [21, 31]. For the prediction of the EDM responses, the empirical models and multi regression models are usually applied. Their interest is, however, the correlation of the surface parameters with the machining conditions and optimizing the EDM process. 1.12 The Research Problems There is little information in sources and researches about EDM processing for the very important and superior specifications of AISI D2 die steel mainly used for cold forming operations industry. As it is well known, the EDM process is a complex superior speeds thermal and metallurgical process in terms of the number of electrical and non-electrical parameters that interfere in it. This study is trying to overcome this problem by studying the process inputs and outputs to reach the best machining conditions for this type of steel for higher productivity, less tool erosion and best surface qualities.

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Another problem is that the surfaces produced from EDM operating with a recast layer containing micro fractures and tensile surface residual stresses which are working to reduce the service lives of molds and their parts. This study attempted to find solutions to this problem without and with the use of additional treatment process after EDM and improve the performance through multiple groups of experiments and through the use of the latest mathematical models and computer simulation programs. The solutions of the above mentioned problems will improve the process conditions, designs, dies lives extension, reducing the production costs and increasing the competitiveness. All these improvements could lead to reduced production costs and annual savings for over hundreds of millions and possibly billions of dollars annually in the areas of global engineering industries for manufacturing machines, equipment, and different goods and for more work opportunities and prosperity. 1.13 The Objectives of This Work The main objectives of this study can be summarized in the following points: 1- Designing and planning an experimental investigation to study the effects of EDM and PMEDM parameters on the mechanical properties of the selected workpiece material, and analyze and verify the experimental results by using the response surface methodology (RSM). 2- Estimating the best surface integrity characteristics for more process productivity, less tool wear and better surface quality. 3- Studying the properties of the created surface residual stresses due to the heat effects, thermal stresses and effects of the recast layer formation on the workpiece machined surfaces. | P a g e 40


4- Determining and reducing the tensile surface residual stresses and improving the average fatigue life by optimizing the machining process parameters. 5- Creating mathematical models in different steps of the study and verifying the accuracy of the experimental results of integrated completion of current research theoretically and experimentally that will help to enrich the work. 6- Analyzing and developing numerical models for verifying the total heat flux generated and fatigue tests results by using the finite element method (FEM) with ANSYS version 15.0 software.

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Chapter

2

LITERATURE REVIEW

2.1 Previous Works on EDM Performances Related with SR, MRR and TWR Wang and Tsai (2001) [32], presented semi-empirical models of MRR for various workpieces (EK2, D2 and H13) and tool electrode combinations (Copper, graphite and silver-tungsten alloy). To achieve higher MRR in EDM, a stable machining process was required, which is partly influenced by the contamination of the gap between the workpiece and the electrode, and it also depends on the size of the eroding surface at the given machining regime. Panda and Bhoi (2005) [33], developed an artificial feed forward neural network to predict MRR of AISI D2 steel. This model performs well under the stochastic environment of actual machining conditions without understanding the complex physical phenomena exhibited in EDM, and provides faster and more accurate results. They found that the 3-4-3-1 neural architecture has the highest correlation coefficient and used it for the analysis. Jaharah et al. (2008) [34], investigated the machining performance of materials, such as SR, TWR and MRR with copper electrode and AISI H13 tool steel workpiece, and the input parameters taken were pulse current and pulse on time, and pulse off time. The optimum condition for SR was | P a g e 42


obtained at low pulse current, pulse on time and pulse off time, and it was concluded that the pulse current is the major factor affecting both the responses, MRR and SR. The prime advantage of employing RSM is the reduced number of experimental runs required to generate sufficient information about a statistically adequate result. M. K. Pradhan and C. K. Biswas (2009) [35], applied the Response surface methodology (RSM) to investigate the effect of four controllable input variables namely: discharge current, pulse duration, pulse off time and applied voltage on EDM surface. Experiments were conducted on AISI D2 tool steel with copper electrode, and the results were analyzed using ANOVA for the level of their significance. Marafona and Araujo (2009) [36], reported their research on effect of the workpiece hardness on the MRR and SR of AISI D2 die steel material. It was suggested that the interaction of workpiece hardness with various factors may be responsible for the variation in MRR. On the other hand, the SR obtained is marginally influenced by the workpiece hardness. The workpiece hardness effect on the MRR is negligible in comparison to other factors. B. B. Patel and K. B. Rathod (2012) [17], tried to focus their attention on the development of a comprehensive mathematical model for correlating the interactive and higher order influences of various EDM parameters through RSM, utilizing the relevant experimental data as obtained through the experimentation of SR. The adequacies of the above proposed model were tested through the analysis of variance (ANOVA). O. Belgassim and A. Abusada (2012) [37], adopted an orthogonal array based on Taguchi method to optimize the EDM parameters. Experimental data were evaluated statistically by analysis of variance (ANOVA). The | P a g e 43


EDM parameters were pulse current, pulse on time, pulse off time and the gap voltage and using AISI D3 workpiece and copper electrode, while the machining responses concerned was the SR of the machined surface. R. Atefi et al. (2012) [38], investigated the influence of different EDM parameters (current, pulse on-time, pulse off-time, gap voltage) on the SR, MRR and TWR as a result of application of copper electrode to cold work die steel DIN 1.2379 (AISI D2). Design of the experiment was chosen with full factorial in finishing stage. They used the artificial neural network to predict the SR ,MRR and TWR. S. R. Nipanikar (2012) [39], reported on the cutting of D3 die steel material using EDM with a copper electrode by using Taguchi methodology to analyze the effect of each parameter on the machining characteristics and to predict the optimal choice for each EDM parameter, such as peak current, gap voltage, duty cycle and pulse on time. The analysis revealed that, in general, the peak current significantly affects the MRR and EWR. P. R. Kubade and V. S. Jadhav (2012) [40], investigated the influence of EDM parameters on TWR and MRR while machining of AISI D3 material. The parameters considered are pulse-on time, peak current, duty factor and gap voltage with a copper electrode. The experiments were planned, conducted and analyzed using Taguchi method. It was found that the MRR is mainly influenced by the peak current; TWR is mainly influenced by the peak current, pulse on time and duty cycle, while gap voltage has much less effect on the electrode wear rate. Gautam K. and Karan C. (2012) [16], observed the microstructure of D3 tool steel before and after heat treatment, and investigated the SR in D3 after EDM. For this set of experiments, three different tool electrodes were | P a g e 44


taken, and the result showed the variation of SR value with respect to discharge current. It was observed that Copper-Tungsten is gives a good quality surface as compared to copper electrode and graphite electrode. Graphite is recommended for roughing, and copper electrode is recommended for semi finishing process. A. Bergaley and N. Sharma (2013) [41], attempted to study the cutting of high carbon and high chromium hard D3 steel by EDM with copper electrode. A work was presented on the performance parameter optimization for MRR and TWR based on DOE and optimization of EDM process parameters. The technique used was Taguchi technique which is a statistical decision making tool which helps in minimizing the number of experiments and the error associated with it. The research showed that the peak current has a significant effect on MRR. Sanjay K. M. et al. (2014) [42], studied the effect of machining parameters, such as pulse on time, pulse off time and discharge current on the MRR, TWR and SR of AISI D2 tool steel. For the experimentation, grey relational analysis and RSM were used. The experiments signified that the parameters of pulse on time, pulse off time and discharge current, have a direct impact on MRR, and with their increase, MRR increases as well. With the increase in pulse off time, TWR decreases. The analysis of results for SR showed that the pulse on time and off time have the highest impact on it. 2.2. Previous Works on Powder mixed EDM (PMEDM) Tzeng and Lee (2001) [43], studied the effect of various powder characteristics on machining of SKD-11 material. The various additives mixed in the working fluid were Al, Cr, Cu and SiC. It was found that the concentration, size, density, electrical resistivity and thermal conductivity | P a g e 45


of powders significantly affect the machining performance. Addition of appropriate amount of powders to the dielectric fluid resulted in increased MRR and decreased TWR. For a fixed concentration of particles, the smallest size of the particle led to highest MRR and lowest TWR. Pecas P. and Henriques E. A. (2003) [44], pointed out the effect of silicon powder mixed dielectric and EDM parameters (peak current, duty cycle, polarity and flushing) on machining AISI D2 die steel workpiece and electrolytic copper electrode. Improvement in surface finish was assessed through quality surface indicators and process time measurements over a set of different processing areas. Kansal et al. (2007) [45], studied the effect of addition of silicon powder on the machining rate of AISI D2 Die Steel and copper electrode. It was found that peak current, concentrati99on of the silicon powder; pulse-on time, pulse-off time, and gain significantly affect the material removal rate in PMEDM. H. K. Kansal et al. (2008) [46], developed a model to calculate the temperature distribution in the workpiece material by employing the ANSYS software in the powder mixed electrical discharge machining. In their presented model, it was assumed that 9% of the total heat was absorbed by the workpiece. The results of finite element simulation were utilized to estimate the material removal rate from workpiece. The usage of introduced temperature dependent material properties was one of the major features of their model which led to a better accuracy in predicting the MRR parameter. S. Prabhu and B. K. Vinayagam (2008) [47], proposed the nano surface finish of AISI D2 tool steel material using multiwall carbon nanotubes in electrical discharge machining process. The surface morphology, surface | P a g e 46


roughness and micro cracks were determined using an atomic force microscope (AFM). S. Prabhu and B. K. Vinayagam (2010) [20], used a single-wall carbon nanotube mixed with dielectric fluids in EDM process to analyze the surface characteristics, like surface roughness, micro cracks in AISI D2 tool steel workpiece material which is very much used in moulds and dies. Khalid H. S. and Kuppan P. (2012) [48], presented the experimental investigations on addition of aluminum metal powder to dielectric EDM. Distilled water was used as dielectric fluid. The workpiece and electrode materials chosen for the investigation were W300 die-steel and electrolytic copper, respectively. Taguchi design of experiments was used to conduct experiments by varying the parameters of peak current, pulse on time, concentration of the powder, and polarity. The process performance was measured in terms of MRR, TWR, average SR, and WLT. The experimental results indicated that the polarity significantly affects the machining performance. B. Reddy et al. (2014) [33], studied the effect of fine metal powders such as aluminum and copper mixed with the dielectric fluid, during EDM of AISI D3 die Steel and EN-31 steel. The workpiece material, peak current, pulse on time, duty factor, gap voltage and mixing of fine metal powders in dielectric fluid were taken as process input parameters. MRR and SR were taken as output parameters to measure the process performance. Taguchi design of experiments was used to conduct the experiments. The obtained outcomes of experiments indicated that the addition of metal powders to the dielectric fluid increases the material removal rate and improves the surface quality.

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2.3 Previous Works on Surface Residual Stresses and Fatigue Strength for EDM Abu Zeid (1997) [49], examined the influence of the EDM pulse current and pulse-on duration parameters on the fatigue life of AISI D6 tool steel. The results showed that the defects in the machined surface result in a significant reduction in the fatigue life. It was also shown that the fatigue life is correlated to the thickness of the white layer and to the presence of surface cracks, both of which were determined by the heat energy supplied per spark during the machining process. Rebelo et al. (1998) [50], reported the formation of plasma channel between the tool (steel) and workpiece, resulting in metallurgical transformations, residual tensile stresses and surface cracking. The dimension of random overlapping surface craters increases with machining pulse energy. The density and penetration depth of the cracks in the re-cast layer increase with the machining pulse energy. The authors measured the residual stress using XRD technique and found similar stress pattern for martensitic steels. The residual stress increases from the bulk material to a maximum and then decreases again near the surface. The greater the discharge energy, the greater the depth at which the maximum value of residual stress occurs. Guu Y.H. and Hocheng H. (2001) [51], presented the effects of titanium nitride (TiN) coated by physical vapor deposition (PVD) to improve the fatigue life of AISID2 tool steel, which was electrical discharge machined (EDM) at various machining parameters, such as pulse current and pulseon duration. They proved that AISI D2 steel coated by TiN exhibited considerably increased surface hardness, a better surface finish, and

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decreased superficial tensile residual stress, or added compressive residual stress on the surface, increasing their fatigue limit. Guu Y. H and Hocheng (2001) [52], studied the effects of machining parameters of a rotary EDM, such as Ip, Ton, and workpiece rotation on MRR and SR, and found them to be increased with the increase in rotational speed. Also, the results are compared with the conventional EDM and found to produce more MRR, improved SR and reduced recast layer. Yadav et al. (2002) [53], developed an FEM model to approximate the temperature field and thermal stresses due to Gaussian heat flux distribution of a spark during EDM of HSS material. The effects of process variables, such as (pulse current and time on) on these responses were reported. It was proposed that the high temperature gradients generated at the gap during EDM result in large localized thermal stresses in a small heat-affected zone leading to micro-cracks, decrease in strength and fatigue life and possibly catastrophic failure. Guu Y. H. et al, (2003) [54], studied experimentally the effect of various machining parameters on the SR, and investigated the surface characteristics and machining damage caused by EDM to AISI D2 die steel. The recast layer was measured using SEM, residual stresses using XRD machine and surface roughness was measured using surface profilometer, and the empirical relations were proposed. It was reported that a HAZ is formed just beneath the recast layer and introduces tensile residual stress on the surface due to the non-homogeneity of heat flow (heated and cooled at a high rate) and metallurgical transformations or to localized inhomogeneous plastic deformation. The experimental results

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indicated that the thickness of the recast layer, and surface roughness are proportional to the power input. Lee et al. (2004) [55], studied extensively the structural change in EDM machined surface by revealing experimentally that the influence of the EDM parameters on the surface integrity of AISI 1045 carbon steel and furnished that average WLT and induced residual stress tend to increase at higher values of pulse current and time on. However, for an extended time on, it was noted that the surface crack density decreases. Besides, obvious cracks are always apparent in thicker white layers. A smaller pulse current tends to increase the surface crack density, while a prolonged time on amplifies the opening degree of the surface crack, thereby reducing the surface crack density. B. Ekmekci et al. (2005) [56], presented procedures and results of experimental work to measure the residual stresses and hardness depth in the EDM surfaces. Layer removal method was used to express the residual stress profile as a function of depth. Thin stressed layers were removed from the machined samples by electrochemical machining. The relational dependence of the machining parameters with residual stresses was obtained, and a semi-empirical model was proposed for plastic mold steel with deionized water as dielectric liquid. These stresses were found to be increasing rapidly with respect to depth, attaining their maximum value, around the yield strength, and then falling rapidly to compressive residual stresses in the core of the material, since the stresses within plastically deformed layers are equilibrated with elastic stresses. Marafona and Chousal (2006) [57], developed a thermal-electrical model using copper and iron as anode and cathode, sparks were generated by electrical discharge in a liquid media, and the obtained results were | P a g e 50


compared with the experimental values of the other researchers. The TWR and MRR as well as SR results agree reasonably well with them. FEA model was employed to estimate the surface roughness and the removed material from both anode and cathode. It was reported that the anode material removal efficiency is smaller than that of the cathode because there is a high amount of energy going to the anode and also a fast cooling of this material. Ekmekci et al (2006) [58], suggested a semi-empirical equation for scaling residual stresses in EDM surfaces and reported that the stress increases from the surface and attains a maximum value, which is approximately equal to the ultimate tensile strength of the material, and then it falls gradually to zero or even to a small compressive residual stress at greater depths. The residual tensile stress increases with the increase in pulse current and pulse-on duration. The formation of surface cracks is attributed to the differentials of high contraction stresses exceeding the material’s ultimate tensile stress within the white layer. Ben Salah et al. (2006) [59], presented a numerical model to study the temperature distribution in the EDM process and used the thermal results for predicting the material removal rate and the total SR. In this study, the fraction of the generated heat entering the workpiece was considered equal to 0.08. Subsequently, they analyzed the numerical results concerning the temperature distribution, the thermal and residual stresses of EDM machined stainless steel AISI 316L workpiece with experimental data, which was in good agreement Salonitis et al. (2009) [60], developed a simple thermal based model for steel (St 37) workpiece and rectangular shape copper tool to determine the MRR and SR, and asserted that the increase in pulse current, gap voltage | P a g e 51


or pulse on time results in higher MRR. Besides, reducing pulse off time increases MRR. It was reported that the model predictions and experimental results are in good agreement. They developed a model for SR and stated that with the increasing in process parameters, pulse current, pulse on time and gap voltage coarser workpiece surfaces are achieved. Later, it was verified experimentally and found to be in good agreement with predicted results. T. Y. Tai and S. J. Lu (2009) [27], performed an experimental investigation to identify the EDM processing parameters which suppress the formation of surface racks in the machined surface of SKD11 die steel (equivalent to AISI H13) specimens. In the EDM trials, the specimens were machined using pulse currents with pulse-on durations. The various specimens were then fatigue tested at loads ranging from 1470 to 2401 N in order to determine their respective fatigue lives. A polished SKD11 specimen was also fatigue tested for comparison purposes. The results showed that increasing the pulse current and reducing the pulse-on duration provide an effective means of up pressing the surface cracking phenomenon. Higher values of the pulse current and pulse-on duration are found to increase the average thickness of the recast layer. F. Ghanem et al. (2011) [61], indicated that the high cycle fatigue tests showed the presence of cracks in brittle white layer, quenched martensitic layer, and a field of tensile residual stresses (+750 MPa) results in a loss of 34% of endurance limit comparatively with the endurance evaluated for the milled state that generates crack-free surfaces. Indeed, the application of wire brushing to EDM surfaces generates compressive residual stresses (≈ −100 MPa) that stabilize the crack networks propagation, and therefore restores to the EDM surfaces their endurance limit value corresponding to | P a g e 52


the milled state. These rates could be further increased by the application of the wire brushing process to the polished surfaces that reached 75% and 30% comparatively to the EDM and milling states, respectively. Agnieszka D. et al. (2012) [62], presented the results of the influence of basic EDM parameters and electrical discharge alloying (EDA) parameters on the surface layer, and also the influence of superficial cold-work treatment applied after the EDM of EDA to the modification of these properties.

The

investigations

included

texture

of

the

surface,

metallographic microstructure, micro hardness distribution, fatigue strength, and resistance to abrasive wear. It was proved that the application of the roto-peen after the EDM and the EDA results in lowering the roughness height up to 70%, the elevation of surface layer micro hardness by 300–700 μHV, and wear resistance uplifting by 300%. J. LO´ PEZ et al (2012) [63], studied the fatigue performance of EDM Ti6Al-4V and, more specifically, the effect of cyclic damage on the static and dynamic tensile properties of the material. In a first step, fatigue failure was studied. Afterwards, tensile tests were performed on specimens that had been previously subjected to cyclic loading during predefined fractions of the fatigue life. In addition to conventional experiments at quasi-static strain rate, dynamic tests were performed using a split Hopkinson tensile bar setup. The results revealed that the early fatigue failure is due to the growth of cracks on the machined edges of the specimens. L. Llanes et al. (2013) [64], focused on assessing the use of two different surface modification routes: thermo mechanical treatments (shot blasting, polishing and final high temperature annealing) and/or physical vapor deposition of hard coatings, for improving the fracture and fatigue strength of an EDM-shaped fine-grained hard metal grade. The experimental results | P a g e 53


indicated that both approaches markedly decrease the lessening effect of EDM on the mechanical strength of hard metals, although a complete fracture and fatigue strength retention are only achieved by combining both of them. Josef S. et al. (2013) [65], presented the work which aims at multi-method characterization of combined surface treatment of Ti-6Al-4V alloy for biomedical use. The surface treatment consisted of consequent use of EDM, acid etching and shot peening. Surface layers were analyzed employing scanning electron microscopy and energy dispersive X-ray spectroscope. Acid etching also created partly nanostructured surface and significantly contributed to the enhanced proliferation of the bone cells. Shot peening significantly improved the poor fatigue performance after EDM. The final fatigue performance is comparable to the benchmark electro polished material without any adverse surface effect. Todd M. M. (2014) [66], presented an experimental study in which the degradation of fatigue strength of Ti–6Al–4V due to improved EDM processing is measured in axial tension at a load ratio of R = 0.1. It was shown that, relative to specimens finely milled, the state-of-the-art EDM processing caused a reduction in fatigue strength by 15–30%. This strength degradation was found to correlate directly with the thickness and roughness of recast layers created by the solidification of melt material formed during EDM. Post-processing with either electrochemical polishing or bead blasting was demonstrated to remove the deleterious effects of EDM, such that specimens possessed intrinsic fatigue behavior as indicated by crack initiation at interior locations. Havlikova J. et al (2014) [20], presented a surface treatment of orthopedic implants combining EDM, chemical milling (etching) and shot peening. | P a g e 54


Each of the three techniques was used or proposed to be used as a favorable surface treatment of biomedical titanium alloys. Fatigue life of the material was determined. EDM and subsequent chemical milling led to a significant improvement osteoblast proliferation and viability. Subsequent shotpeening significantly improved the fatigue endurance of the material. The combined surface treatment is therefore promising for a range of applications in orthopedics. 2.4 Concluding Remarks From the previous literature survey, the main conclusions can be drawn as follows: 1. The present work attempted to review different scientific theoretical and practical researches to cover the most important topics of this thesis. 2. (13) research works have been studied and reviewed in the field of study and evaluation of the performance parameters (MRR, TWR and SR) of the process. 3. (8) research works have been studied and reviewed in the field of study and evaluation of the performance parameters of the process with the addition of mixing powders (PMEDM). 4. (20) research works have been studied and reviewed in the field of studying and evaluation of the total heat flux generation, the surface recast white layer, surface micro cracks, surface residual stresses and fatigue life modeling and improving. 5. The main conclusions from the examination of these sources show that there are a limited number of research works dealing with different steel types used for manufacturing molds and dies, especially the ultra-important type AISI D2 die steel for cold works | P a g e 55


in the area of performance parameters, the addition of mixing powders (PMEDM), surface study after EDM and PMEDM for residual stresses and fatigue life and related modeling works. 6. It was unable to find any research works related to study the effect of adding silicon carbide powder on EDM machining for any type of steels, as well as any other type of steels for molds and dies, specially the type AISI D2. 7. It was unable to find any research works related to study and examine the effect of adding any kind of mixed powders on the inducing of surface residual stresses and the fatigue life of the steel workpieces and of any kinds of the engineering ferrous and nonferrous materials. 2.5 The role of Present Work 1. Using SiC powder for machining and modeling AISI “D” and “H” die steel grades by EDM or PMEDM processes. 2. Using the powder mixing to dielectric fluid (PMEDM) process in determining and modeling the induced surface residual stresses, fatigue life, WLT and total heat flux by using or not using the RSM and FEM by ANSYS software, including the effect of shot blast peening after EDM processing using the RSM and FEM by ANSYS software. 3. Using the graphite electrodes for EDM and PMEDM machining and modeling the AISI D2 die steel, including the later treatment by shot blast peening processes and for determining the induced surface residual stresses, fatigue life, WLT and total heat flux by using the RSM and FEM by ANSYS software.

| P a g e 56


Chapter

3

NUMERICAL ANALYSIS 3.1 Introduction Various theoretical and numerical approaches have been proposed for explaining the basic phenomenon of the EDM and PMEDM processes, but a comprehensive quantitative theory concerning the mechanism of material removal cannot be formulated [67]. The theoretical model must consider the important aspects of the process, such as conduction, convection, thermal properties of material with temperature, the latent heat of melting and evaporation, the percentage distribution of heat between tool, workpiece and dielectric fluid and the thermal proper of electrodes. The Gaussian distribution of heat flux based on discharge duration has been used to develop and calculate a numerical model of the EDM process and to investigate the effect of machining parameters on the temperature distribution, thermal stresses and subsequently surface residual stresses and fatigue life in EDM and PMEDM process. 3.2 Theory and Formulation During the spark, the dielectric medium breaks down and the current starts flowing between the electrode and workpiece. A previous study mentioned that the EDM is physically similar to many gas discharges in which a constant current is passed through the plasma [68]. Due to the | P a g e 57


random, high complexity and uncertainty nature of EDM, the following assumptions have been considered to make the problem mathematically feasible for all proposed EDM and PMEDM models unless otherwise is specified: 1- An axisymmetric model has been considered. 2- Workpiece materials are homogeneous and isotropic in nature [51]. 3- The material properties of the workpiece and tool are temperature dependent. 4- Density and element shape are not affected [69]. 5- EDM discharge spark channel is considered as a uniform cylindrical column shape. 6- The heat source is assumed to have Gaussian distribution of heat flux on the surface of the workpiece material during pulse on time period [10-11]. 7- Temperature analysis is considered to be of transient type [51, 70]. 8- The channel diameter is approximately between 10 µm and 100 µm thus, the electrode can be considered as a semi-infinite body. 9- The magnitude of the heat flux incident on the electrodes is independent of the affected surface profile. 3.3. Thermal Modeling of EDM and PMEDM Processes Many researchers analyzed the material removal by heat conduction models with a heat source acting on the surface of electrode during a single electrical discharge [71]. The energy generated by electrical discharge is allocated at the anode, the cathode, and the plasma column. Figure (3-1) shows the idealized case where the workpiece is being heated by a heat source with Gaussian distribution. The various assumptions are made to simplify the random and complex nature of EDM, and as it simultaneously | P a g e 58


interacts with the thermal, mechanical, chemical and electromagnet phenomena [72]

3.3.1. The governing equation The Fourier heat conduction equation was used as the governing equation. This equation is used as the base of the thermal modeling for describing the state of heat distribution during each discharge [51,73], governed by the following thermal diffusion differential equation [73]:

ρCp

𝜕𝑇 𝜕𝑡

=

1

𝜕

𝑟 𝜕𝑟

(𝑘

𝜕𝑇 𝜕𝑟

)+

𝜕 𝜕𝑧

(𝑘

𝜕𝑇 𝜕𝑧

)

(3-1)

where, 𝑇 is temperature in (K), 𝑡 is time, ρ is the density of workpiece material, 𝑘 is thermal conductivity of the material (J/mK s), Cp is specific heat capacity of workpiece material in solid state (J/kg K) and r and z are coordinate axes as shown in Figure (3-1).

Figure (3-1): Schematic sketch of Gaussian heat distribution for the thermal model in EDM and PMEDM process [45]

| P a g e 59


3.3.2. The heat flux due to a single spark Many authors have considered uniformly distributed and the hemispherical disc heat source within a spark [74]. This assumption is far from reality for thermal modeling in EDM. However, DiBitonto et al. [10], Eubank et al. [75] and Bhattacharya et al. [76] have shown that the Gaussian heat distribution is more realistic than disc heat source for modeling the heat input in EDM. This fact is evidenced from the actual shape of a crater formed during EDM. 3.3.3. Boundary conditions The workpiece is represented by a semi-infinite rectangle bounded by four boundaries B1, B2, B3 and B4, as shown in figure (3-2). The coordinate workpiece axes are r and z, where z is the axis of symmetry, so

Figure (3-2): The thermal model of EDM and PMEDM processes [45] | P a g e 60


taking advantage of its symmetry; a small half-plane is cut from the workpiece (CDEF) with negligible thickness. The process consists of heating period (Ton) and cooling period (Toff). In the considered workpiece domain, the heat transferred to the workpiece is represented by a Gaussian heat flux distribution during the single spark on time that is applied to the top surface B1 to spark radius R. On the remaining region on B1 surface, the convection heat transfer takes place due to the cooling effect caused by the dielectric fluid with or without adding of powder mixed and ambient air. As the boundaries B2 and B3 are very far from the spark radius and also the spark has been made to strike for a very short moment, no heat transfer conditions have been assumed for them. For B4, which is the axis of symmetry, the heat flux has been taken as zero as there is no net heat gain or loss from this region. The boundary conditions for heating and cooling period in the domain of heat flux are given as follows: Initial condition: when 0< 𝑡 ≤ 𝑇𝑜𝑛 1. For boundary B1; up to spark radius, R: if r = R , [45]

𝐾

𝜕𝑇 𝜕𝑧

= 𝑄𝑤(𝑟)

(3-2)

Beyond spark radius, R: if r > R

𝐾

𝜕𝑇 𝜕𝑧

= ℎ(𝑇 − 𝑇0 )

(3-3)

=0

(3-4)

For off time:

𝐾

𝜕𝑇 𝜕𝑡

2. For boundary B2, B3, B4: 𝜕𝑇 𝜕𝑡

=0

(3-5) | P a g e 61


where, R is the radius of spark (plasma channel), h is the heat transfer coefficient between the workpiece surface and dielectric or for powder mixed dielectric, 𝑄𝑤(𝑟) is the heat flux entering the workpiece during the pulse on-time and it has a zero magnitude during the pulse off-time, 𝑇0 is the initial temperature of the dielectric fluid in which the electrodes are submerged which is equal to room temperature (298 K). 3.3.4. The heat flux in EDM and PMEDM The probability density function (pdf) of Gaussian distribution for a random variable of (r) as shown in figure (3-3) is given by the following relation [77]:

𝑃(𝑟) =

1 √2𝜋.𝛿

𝑒

−

𝑟² 2𝜎²

(3-6)

where, P(r) is the intensity of heat imparted to the workpiece surface and ( 𝟏/(√𝟐𝝅. 𝛿) is the peak value of the distribution and 𝛿 is the standard

deviation. Since the Gaussian curve does not mathematically become zero until infinity, it becomes necessary to select some finite large value of its argument to represent the bottom of the crater. Usually six times of 𝛿 (−3 𝛿 to +3 𝛿) is taken for dropping the response to 0.25% of its initial value i.e. 99.75% of the values lies between r = μ−3 𝛿 and r = μ+3 𝛿. The profile of a three-dimensional crater can be obtained by rotating the Gaussian curve around the vertical axis. Therefore, R = 3 𝛿. Substituting the value of 𝛿 into equation (3-6) yields:

𝑃(𝑟) =

3 √2𝜋.𝑅

𝑒

−4.5

𝑟² 𝑅²

(3-7)

To consider the effect of suspended powder particles into dielectric fluid on PMEDM, the intensity of heat imparted to the workpiece surface, | P a g e 62


𝜹

𝜹

Figure (3-3): The Gaussian distribution [45] is denoted by (Qw ) and is a function of r. At r = 0, P(r) = Q0; where (Q0) is the maximum intensity of heat applied at the axis of a spark (center of the workpiece) and its radius (R), then the heat flux Q w(r) at radius r of the system (equation (3-7)) is given by:

𝑄𝑤(𝑟) = 𝑄0𝑒

−4.5

𝑟² 𝑅²

(3-8)

The rate of energy incident on the workpiece is equal to the rate of energy supplied which is equal to Rw *Vb *Ip * Kn . where, Rw is the energy percentage fraction of heat input to the workpiece, Vb is the breakdown voltage (different from the applied voltage), R is the spark | P a g e 63


radius in µm, Ip is the discharge current and Kn is a new parameter introduced to take into account the effect of suspended powder particles on the spark frequency and breakdown voltage. The value of Kn depends upon the type of powder, powder properties, such as shape, size, concentration, etc. Then, the substitution into equation (3-8), the heat flux entering the workpiece due to spark energy of EDM assumed to be Gaussian distribution can be represented by the following equation [55]:

𝑄𝑤(𝑟) =

4.57∗𝑅𝑤∗𝑉𝑏 ∗𝐼𝑝 ∗ 𝐾𝑛 𝜋.𝑅²

𝑒

−4.5

𝑟² 𝑅²

(3-9)

Where, the (Rw) is the value that has been determined by Yadav et al. [53] to be as (0.08) for their theoretical work of conventional EDM and the same value was used in this work. The value (Vb) is taken as (20 V), (R ) as (15 µm) and (Qw(r) =680 MW/m²k) for various values of discharge current. 3.3.5. Energy partition (Rw) due to EDM between cathode, anode and dielectric liquid This is an important parameter required for the percentage of heat input distributed between the cathode, anode, and dielectric. DiBitonto et al. [10] and Patel et al. [11] have suggested that a constant fraction of total power is transferred to the electrodes. They have used the value of Rw as 8% as the percentage of heat input absorbed by the workpiece for their theoretical work. Shankar et al. [69] have calculated that about 18% is absorbed by cathode and the rest is discharged to the dielectric fluid. In the present work, Rw is taken as 0.08.

| P a g e 64


As explained earlier, the powder particles suspended into the dielectric fluid increase the electrical conductivity of the dielectric fluid and help to spread the discharge uniformly in all directions. As a result, the fraction of the energy transferred to the workpiece (Rw) may be larger than that of EDM. However, there is no theoretical and experimental method to calculate the value of (Rw) during the PMEDM. In the present model, it has been assumed that 9% of the total heat is lost to the workpiece. 3.3.6. Discharge channel radius and profile The size of plasma channel is not constant but it grows with time [10], depending upon various factors, such as electrode material, arrangement and polarity [78]. Measurement of the spark radius is extremely difficult due to very high pulse frequencies and very short pulse duration. Some researchers have tried theoretically and experimentally to determine the spark radius (R) in EDM [79-80]. DiBitonto et al. have calculated the radius of the discharge channel mathematically in the form of integral equation for rectangular pulses [10]. Ikai and Hashiguchi [81] showed that the discharge radius is related to the current intensity and pulse on duration time. Marafona et al. [57] chose the discharge radius based on the work of Ikai and Hashiguchiand and suggested an equation called the equivalent heat input radius R(t) or the radius of plasma channel (mm), which is dependent on the current intensity (I) and pulse on duration (Ti), and is given here [57]:

R(t)=2.04*Ip0.43*Ton0.44

(3-10)

This assumption is important to determine the radius of the discharge channel (spark) for each input current intensity case. In PMEDM, the powder mixed into the dielectric fluid helps the discharge to spread uniformly in all directions, resulting in an enlarged and | P a g e 65


widened discharge channel. Experimental studies on PMEDM revealed that the spark gap is enlarged and widened by a factor of 2 or 3 of conventional EDM [78, 82]. However, a reliable and realistic method of determining the spark radius by either theoretical/experimental analysis has not been reported. In this work, the radius of the spark for PMEDM suggeste that the value of R taken to be 30%–50% larger than that found by Marafona et al. [57]. 3.3.7. The latent heat In EDM and PMEDM, the electrode and workpiece are repeatedly heated above the melting points and are allowed to cool in the dielectric fluid. This causes a change in the phase of the materials. The phase change requires an energy input equivalent to the latent heat. The specific heat for melting and evaporation is modified as given below by incorporating the latent heat of melting and evaporation [77].

Cm = Cp+ Cev = Cm+

𝐿𝑚

2∆𝑇 𝐿𝑒𝑣

2∆𝑇

for Tm-∆𝑇 ≤ T ≤Tm+∆𝑇

(3-11)

for Tev-∆𝑇 ≤ T ≤Tev+∆𝑇

(3-12)

where, Cp is specific heat of workpiece, Cm is specific heat in melting state,

Cev is specific heat in evaporation state, 𝐿𝑚 is latent heat due to melting and 𝐿𝑒𝑣 is latent heat due to evaporation. 3.3.8. Spark frequency and breakdown voltage Spark frequency is a measure of the number of times the discharge strikes against the surface of the workpiece. In the case of PMEDM, the powder suspended in the dielectric fluid gets energized and behaves in a zigzag fashion. The suspended powder particles enlarge and widen the spark gap between both the electrodes and change the ionization–deionization | P a g e 66


characteristics of the dielectric fluid, as shown in figure (3-4). With increase in the gap distance, an appropriate reduction in the breakdown voltage (electrostatic capacity) occurs, which results in more discharges per unit time (spark frequency). Experimentally, it has been found that in PMEDM, the discharge frequency is about 2–3 times higher than that in EDM, whereas the breakdown voltage is about 20%–30% lower than that for EDM process [73, 83]. The increased spark frequency and reduced voltage produce more small and shallow craters. The reason is that energy available for material removal during a given period is shared by a large number of powder particles, and the magnitude of the impact force, which acts on the workpiece surface, is smaller than the conventional EDM. Figure (3-4a) shows that the size of the crater produced by EDM is big and its surface is rough. However, in PMEDM, the craters are shallow and smaller in size as shown in figure (3-4b).

Figure (3-4): The spark frequency in: (a) EDM, (b) PMEDM [84] 3.3.9. Thermal stress distribution The local thermal expansion of workpiece material resulting from the extreme temperature gradients that occur during EDM results in extreme nonuniformities which lead to high thermal stresses. The transient temperature distribution in the workpiece, obtained by solving the heat | P a g e 67


conduction equation along with the boundary and initial conditions, is used as input for the calculation of thermal stresses. Due to intense heating of the workpiece material during sparking period, high stresses are locked in the workpiece. These stresses are known as thermal stresses and are introduced at the end of heating period. Thermal stresses are presented by varying the two parameters, i.e., pulse current and the pulse on duration time, because during the pulse duration, the heat flux is supplied to the workpiece for a very short duration (in μs). Thus, the area nearer to the spark expands significantly. However, the surrounding materials which are not able to expand instantaneously, will restrain them, causing compressive thermal stresses. Here, Gaussian heat flux distribution is used for the calculation of temperature distribution. However, it was impossible to validate the thermal stress distributions in the workpiece, as no results (experimental/theoretical) are available for thermal stresses developed during EDM. It corresponds to the nature of the thermal stress variation in the radial direction along the center line of workpiece [53, 59]. 3.4. Surface Residual Stress Distribution Residual stresses are stresses which can exist in a body when it is free from external forces. They are produced whenever a body undergoes non uniform plastic deformation. Residual stress tends to changing by the occurrence of metallurgical alteration related to volumetric changes. The austenite transformation to martensitic results in increase in specific volume of about 3% [85]. Tensile surface residual stresses develop near the surfaces of the workpiece due to sharp temperature gradient caused by the rapid thermal cycle at the surface and thermal contraction of re-solidified material on the base material, in combination with plastic deformation and | P a g e 68


non-homogeneity of heat flow with metallurgical transformations in EDM. They are caused by incompatible internal permanent strains, and typically produce large tensile stresses whose maximum value is approximately equal to the yield strength, balanced by lower compressive residual stresses elsewhere in the component. The rapid heating and cooling cycle leads to dramatic structural changes. High thermal contraction rates cause severe slip, twining and cleavage on or near the crater depending on the crystal structure [86]. 3.5. Modeling and Simulation of the Total Heat Flux in EDM and PMEDM Processes by Using FEM 3.5.1. Introduction Finite Element Method (FEM) is a powerful tool for computer prediction and obtaining the approximate solution of real engineering problems [57,87]. It can handle a wide range of engineering problems of complex geometry, materials, loading and boundary conditions. It has many finite element analysis capabilities, ranging from a simple, linear, static analysis to a complex, nonlinear, transient dynamic analysis in the fields, such as structural mechanics, thermal systems, fluid mechanics, and electromagnetics [87]. It uses discretization of a continuum domain into finite numbers of parts called elements and seeks solution at discrete points of the domain (nodes) using certain interpolation functions to approximate the primary variables over various elements of the domain. In this work, an axisymmetric three-dimensional model was developed to predict the main aspects of the EDM and PMEDM processes, including the heat flux generation by the discharge sparks, which are absorbed by the workpiece, the electrode and the dielectric fluid and to analyze and model the workpiece fatigue properties that occur in the | P a g e 69


material due to large deformations and transient operation which represents one of the main performance factor of the process. The numerical calculations and experimental results have been used to analyze and compare the performance of EDM with PMEDM processes. The important features and parameters of the process, such as material properties, the pulse on/off duration time, the pulse current, the type of the electrodes and the type and concentration of powders mixing to dielectric are taken into account in the development of the model. In the present work, the commercial FEM ANSYS 15.0 software package was used for developing and solving the project objective models introduced by using the FEM procedures. 3.5.2. Applications of FEM to thermal modeling of EDM and PMEDM processes The applications of FEM to developing and numerically analyzing the thermal models of EDM and PMEDM processes have been implementing by using the transient thermal ANSYS analysis, where the total heat power has to be determined on the basis of time and temperature profile dependent due to a spark discharge profile progressing. Axisymmetric three-dimensional finite models were created with global dimensions of the workpiece, electrode and the dielectric. The model is employed with triangle element type for the thermal analysis. A nonuniformly distributed finite element mesh with elements mapped towards the heat-affected regions was meshed. Due to the workpiece material’s temperature and thermo-physical properties dependent, this type of problem is of nonlinear characteristic. The workpiece undergoes a heating and cooling cycle, modelled by two load steps, namely, heating period and

| P a g e 70


cooling period. The heating period Ton was selected in this work to be 120 μs and cooling period Toff = 40μs. The application of FEM to thermal modeling of EDM and PMEDM numerical analysis carried out based on the variation of temperature due to heat flux generation has been implemented by the Gaussian heat flux distribution during the total discharge sparks of the EDM process with respect to changing voltage and current conditions with time. The loading conditions applied are the temperatures variation and the heat flux convection which varied between nodes. The temperature dependency of material properties was taken into account in the simulation stage. The size of domain for the thermal analyses was dependent on the input parameters of EDM process, since the radius of discharge channel was determined based on the machining settings. For applying the heat flux varying with time on the work domain, a discontinuous method for discretization in time has been utilized by employing an arbitrary polynomial order. Let t0 < t1