كتاب Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods - Volume 2
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 كتاب Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods - Volume 2

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عدد المساهمات : 18799
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تاريخ التسجيل : 01/07/2009
الدولة : مصر
العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى

كتاب  Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods - Volume 2  Empty
مُساهمةموضوع: كتاب Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods - Volume 2    كتاب  Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods - Volume 2  Emptyالثلاثاء 24 أكتوبر 2023, 6:53 am

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أحضرت لكم كتاب
Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods - Volume 2
R. Venkata Rao

كتاب  Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods - Volume 2  D_m_i_13
و المحتوى كما يلي :


Contents
1 Multiple Attribute Decision Making in the Manufacturing
Environment 1
1.1 Importance of Multiple Attribute Decision Making
in the Manufacturing Environment . 1
1.2 Some Important Decision Making Situations
of the Manufacturing Environment . 2
1.3 Multiple Attribute Decision Making Methods . 3
1.4 Overview of the Book . 5
References 5
2 Improved Multiple Attribute Decision Making Methods 7
2.1 Improved Analytic Hierarchy Process Method . 7
2.1.1 Formulating the Decision Table 8
2.1.2 Deciding Weights of the Attributes . 8
2.1.3 Calculating Composite Performance Scores . 10
2.2 Improved Technique for Order Preference by Similarity
to Ideal Solution Method . 10
2.2.1 Formulating the Decision Table 10
2.2.2 Deciding Weights of the Attributes . 11
2.2.3 Calculating Composite Performance Scores . 11
2.3 Data Envelopment Analysis Method 12
2.3.1 The Basic CCR Model 14
2.3.2 Strengths and Limitations of Basic CCR Model 15
2.3.3 Reduced CCR Model . 16
2.3.4 Improved RCCR/Assurance Region Model 16
2.4 Improved Preference Ranking Organization Method
for Enrichment Evaluations 17
2.4.1 Formulation of Decision Table 18
2.4.2 Deciding Weights of the Attributes . 18
2.4.3 Improved PROMETHEE Calculations . 18
ix2.5 Improved ELimination Et Choix Traduisant
la REalité Method 21
2.5.1 Construction of the Decision Table . 22
2.5.2 Calculating the Weights of the Attributes
Using AHP 22
2.5.3 Calculations Using ELECTRE for Final Ranking . 22
2.6 Improved COmplex PRoportional ASsessment Method . 24
2.6.1 Construction of the Decision Table . 25
2.6.2 Calculating the Weights of the Attributes
Using AHP 25
2.6.3 COPRAS Calculations for Final Ranking . 25
2.7 Improved Gray Relational Analysis Method 27
2.8 Improved Utility Additive Method . 30
2.9 VIKOR Method 33
2.10 Improved Ordered Weighted Averaging Method . 35
References 38
3 Applications of Improved MADM Methods to the Decision Making
Problems of Manufacturing Environment . 41
3.1 Applications of the DEA RCCR/AR Method 41
3.1.1 Material Selection for a Given
Engineering Application . 41
3.1.2 Metal Stamping Layout Selection 46
3.1.3 Modern Machining Method Selection 49
3.1.4 Product End-of-Life Scenario Selection 50
3.2 Applications of the Improved PROMETHEE Method 52
3.2.1 Environment Friendly Cutting Fluid Selection
for a Given Machining Application . 52
3.2.2 Evaluation of Environmentally Conscious
Manufacturing Programs . 57
3.2.3 Product End-of-Life Scenario Selection 60
3.2.4 Rapid Prototyping System Selection . 62
3.2.5 Gear Material Selection . 64
3.2.6 Flexible Manufacturing System Selection . 66
3.2.7 Material Handling Equipment Selection 67
3.3 Applications of the Improved ELECTRE Method 69
3.3.1 Machine Tool Selection . 69
3.3.2 Facility Location Selection . 73
3.4 Applications of the Improved COPRAS Method . 74
3.4.1 Material Selection for Given
Engineering Application . 74
3.4.2 Rapid Prototyping System Selection . 76
x Contents3.5 Applications of the Improved AHP Method 77
3.5.1 Environmentally Conscious Manufacturing
Program Selection . 77
3.5.2 Selection of Electroplating System 81
3.6 Applications of the Improved GRA Method 85
3.6.1 Material Selection for a Given
Engineering Application . 85
3.6.2 Rapid Prototyping Process Selection 92
3.6.3 Plant Layout Design Selection . 96
3.6.4 Product Design Selection of a Power
Electronic Device . 101
3.7 Applications of the Improved UTA Method 104
3.7.1 Machine Group Selection in a Flexible
Manufacturing Cell 104
3.7.2 Vendor Selection 112
3.8 Applications of the Improved VIKOR Method 120
3.8.1 Plant Layout Design Selection . 120
3.8.2 Rapid Prototyping System Selection . 122
3.9 Applications of Improved OWA Method 123
3.9.1 Machine Group Selection in a Flexible
Manufacturing Cell 123
3.9.2 Vendor Selection 126
References 130
4 A Novel Subjective and Objective Integrated Multiple
Attribute Decision Making Method 137
4.1 Proposed Novel Multiple Attribute Decision
Making Methodology 137
4.1.1 Preparation of the Decision Table 138
4.1.2 Determination of Weights of Importance
of the Attributes 138
4.1.3 Computation of Preference Index . 140
4.1.4 Final Selection . 140
4.2 Application of the Novel Subjective and Objective Integrated
Method to the Problems of Manufacturing Environment 141
4.2.1 Material Selection for a High Speed Naval Craft 141
4.2.2 Material Selection of a Flywheel . 145
4.2.3 Material Selection of a Cryogenic Storage Tank 148
4.2.4 Industrial Robot Selection 149
4.2.5 Environment Friendly Cutting Fluid Selection
for Given Machining Application 152
4.2.6 Flexible Manufacturing System Selection . 153
4.3 Discussion 154
References 156
Contents xi5 A Novel Weighted Euclidean Distance-Based Approach . 159
5.1 Weighted Euclidean Distance Approach . 159
5.2 Applications of Proposed WEDBA Method for Decision
Making in the Manufacturing Environment . 164
5.2.1 Material Selection of a Flywheel . 164
5.2.2 Robot Selection for a Given Industrial Application 167
5.2.3 Flexible Manufacturing System Selection . 172
5.2.4 Optimum Parameters Selection of Green Electric
Discharge Machining . 183
5.2.5 Selection of Best Product End-of-Life Scenario . 187
References 189
6 A Combinatorial Mathematics-Based Decision Making Method . 193
6.1 Combinatorial Mathematics-Based Approach (CMBA) . 193
6.2 Applications of CMBA to the Decision-Making Problems 195
6.2.1 Selection of Electroplating System 195
6.2.2 Robot Selection . 196
6.2.3 Welding Process Selection . 199
References 202
7 Comparison of Different MADM Methods for Different Decision
Making Situations of the Manufacturing Environment . 205
7.1 Evaluation of Environmentally Conscious
Manufacturing Programs 205
7.2 Rapid Prototyping System Selection 207
7.3 Gear Material Selection 208
7.4 Flexible Manufacturing System Selection 209
7.5 Vendor Selection: An Industrial Case Study 210
7.6 Plant Layout Design Selection 213
7.6.1 Application of Improved AHP Method . 214
7.6.2 Application of Improved GRA Method 215
7.6.3 Application of Improved UTA Method . 215
7.6.4 Application of Improved OWA Method 217
7.6.5 Application of Improved VIKOR Method . 217
7.6.6 Application of WEDBA Method . 218
7.7 Application of CMBA Method . 218
7.8 Warehouse Selection 220
7.8.1 Application of Improved AHP Method . 224
7.8.2 Application of Improved GRA Method 225
7.8.3 Application of improved UTA Method . 225
7.8.4 Application of Improved OWA Method 227
7.8.5 Application of Improved VIKOR Method . 229
7.8.6 Application of WEDBA Method . 230
7.8.7 Application of CMBA Method 230
xii Contents7.9 ECM Program Selection Using Few More MADM Methods . 232
7.9.1 Application of Improved GRA Method 232
7.9.2 Application of Improved UTA Method . 233
7.9.3 Application of Improved OWA Method 236
7.9.4 Application of Improved VIKOR Method . 237
7.9.5 Application of WEDBA Method . 239
7.9.6 Application of CMBA Method 240
References 241
8 Concluding Remarks 243
References 248
Appendix A: Development of fuzzy scales 249
Appendix B: Computer Programs . 255
Index 291
Contents xiii
Index
A
Analytic hierarchy process (AHP), 7–9, 11,
13, 17, 18, 22, 25, 29, 32, 33, 48–50,
55, 57, 58, 60, 61, 65, 70, 71, 74,
77–80, 82–84, 86, 92, 94, 96, 98, 102,
103, 105, 112, 113, 139, 151, 153, 162,
169, 171, 173, 174, 179, 181, 193–195,
200, 205, 207, 212, 214, 215, 220, 224,
225, 230, 232, 233, 239–241, 243–245,
247
C
CCR, 14–17, 60, 80
CCR (RCCR), 16, 41–43, 46, 50, 52, 60
Combinatorial mathematics based approach
(CMBA), 193–196, 198, 202, 218–220,
230–232, 240, 241, 245, 247
Complex proportional assessment (COPRAS),
24, 25, 27, 74, 76, 86, 205, 207, 212,
241, 243, 247
Compromise ranking method, 33, 60, 86, 244
Cutting fluid, 3, 52–54, 56, 152, 153
D
Data envelopment analysis (DEA), 12–17, 21,
41–43, 46, 48–50, 52, 57, 59, 60, 77,
80, 96, 99, 112, 113, 121, 122, 149,
153, 173, 176, 178, 198, 205, 207, 208,
241, 243, 247
E
Electric discharge machining, 49, 183
Electroplating system, 81–84, 195, 196
Elimination Et Choix Traduisant la Realité
(ELECTRE), 21, 22, 52, 60–62, 65, 66,
69–73, 85, 86, 145, 147, 164, 167, 168,
170, 187, 189, 205, 209, 212, 241, 243,
247
Environmentally conscious manufacturing
program, 77
F
Facility location, 73
Flexible manufacturing cell, 104
Flexible manufacturing system, 66, 153, 172,
209
Fuzzy scale, 33, 83, 94, 222
G
Gear material, 64, 208
Gray relational analysis (GRA), 27–30, 85, 87,
90–92, 94, 95, 97–99, 103, 122, 215,
220, 225, 232, 233, 241, 243, 244, 247
I
Industrial robot, 149, 167
M
Machine tool, 69
Material handling equipment, 67
Material selection, 41, 74, 85, 141, 145, 148,
164
Metal stamping layout, 46
M (cont.)
Modern machining method, 49
Multiple attribute decision making (MADM),
13, 14, 24, 33, 35–37, 41, 64, 85, 97,
111, 126, 137, 142, 144, 155, 159, 202,
205–212, 214, 219, 232, 243–245, 247
O
Ordered weighted averaging (OWA), 35, 36,
123, 130, 217, 227, 236, 237, 241, 247
P
Plant layout design, 96, 97, 120, 213
Preference ranking organization method for
enrichment evaluations (PROMETHEE), 17, 18, 20, 52, 60, 61, 63–67,
69, 189, 205, 207, 241, 243, 247
Product design, 101
Product end-of-life scenario, 50, 60
R
Rapid prototyping system, 62, 76, 122, 207
RCCR/Assurance Region, 16
S
Subjective and objective integrated, 86, 245
T
Technique for order preference by similarity to
ideal solution (TOPSIS), 10, 50, 62, 64,
84–86, 91, 93, 95, 97, 99, 105, 113,
122, 123, 147, 149, 168, 170, 179, 186,
196, 205
U
Utility additive method (UTA), 30, 31, 33,
104, 111, 113, 119, 215, 217, 220, 225,
227, 232, 233, 235, 241, 243, 244, 247
V
Vendor, 112, 113, 126, 210, 211
VIKOR, 33, 34, 35, 57, 78, 86, 113, 120–123,
145, 147, 164, 167, 168, 217, 229, 231,
237, 244
W
Warehouse, 220, 224, 225, 227–232
Welding process, 199
Weighted Euclidean distance based approach
(WEDBA), 159, 162, 164, 166–168,
170–173, 175, 176, 178–180, 182, 183,
184, 186, 187, 189, 218, 220, 230, 232,
239, 245


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