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Operations and Production Systems with Multiple Objectives [Kõva köide]

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(Case Western Reserve University)
Teised raamatud teemal:
Operations and Production Systems with Multiple ObjectivesSuurem pilt
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Püsilink: https://www.kriso.ee/db/9780470037324.html
Märksõnad:
The first comprehensive book to uniquely combine the three fields of systems engineering, operations/production systems, and multiple criteria decision making/optimization

Systems engineering is the art and science of designing, engineering, and building complex systemscombining art, science, management, and engineering disciplines. Operations and Production Systems with Multiple Objectives covers all classical topics of operations and production systems as well as new topics not seen in any similiar textbooks before: small-scale design of cellular systems, large-scale design of complex systems, clustering, productivity and efficiency measurements, and energy systems.

Filled with completely new perspectives, paradigms, and robust methods of solving classic and modern problems, the book includes numerous examples and sample spreadsheets for solving each problem, a solutions manual, and a book companion site complete with worked examples and supplemental articles.

Operations and Production Systems with Multiple Objectives will teach readers:





How operations and production systems are designed and planned How operations and production systems are engineered and optimized How to formulate and solve manufacturing systems problems How to model and solve interdisciplinary and systems engineering problems How to solve decision problems with multiple and conflicting objectives

This book is ideal for senior undergraduate, MS, and PhD graduate students in all fields of engineering, business, and management as well as practitioners and researchers in systems engineering, operations, production, and manufacturing.

Arvustused

Operations and Production Systems with Multiple Objectivesis very easy to read, and each chapter starts with an introduction and ends with a summary and a well-selected list of references.  (IEEE Systems, Man, & Cybernetics Magazine, 1 April 2015)

Preface xxvii
Acknowledgment xxxiii
1 Introduction
1(48)
1.1 Introduction
1(4)
1.1.1 Overview of Input and Output Systems
2(1)
1.1.2 Overview of the
Chapters of This Book
3(2)
1.2 Production and Operations History and Perspective
5(3)
1.3 Production and Operations Models
8(8)
1.3.1 Production and Operations Planning
9(4)
1.3.2 Process Design and Logistics
13(2)
1.3.3 Quality, Reliability, and Measurement
15(1)
1.4 Systems Approach and Tools
16(5)
1.4.1 Systems Approach
16(1)
1.4.2 Multicriteria Decision Analysis
17(2)
1.4.3 Problem-Solving Tools
19(2)
1.5 Multicriteria Production/Operation Systems
21(5)
1.5.1 Pyramid of Multicriteria Production/Operations
21(3)
1.5.2 Hierarchical Multicriteria Planning
24(2)
1.6 Product and Process Life Cycle
26(3)
1.6.1 Product Life Cycle
26(1)
1.6.2 Process Life Cycle
27(1)
1.6.3 Product-Process Matrix
28(1)
1.7 Learning Curves
29(4)
1.7.1 Arithmetic Approach
30(1)
1.7.2 Logarithmic Approach
31(1)
1.7.3 Deteriorating Curves
32(1)
1.8 Capacity Planning
33(3)
1.8.1 Capacity Strategies
33(1)
1.8.2 Break-Even Analysis
34(2)
1.9 Machining/Operation Optimization
36(13)
1.9.1 Taylor's Tool Life Equation
37(1)
1.9.2 Multicriteria of Machining Operation
38(2)
References
40(2)
Exercise
42(7)
2 Multicriteria Decision Making
49(96)
2.1 Introduction
49(5)
2.1.1 Decision Process Paradigm
51(2)
2.1.2 Decision-Making and Process Pyramid
53(1)
2.1.3 Decision-Making Paradigm
53(1)
2.2 Efficiency and Its Extensions
54(8)
2.2.1 Efficiency (Nondominancy/Pareto Optimality)
56(1)
2.2.2 Polyhedral Graphical Efficiency
57(1)
2.2.3 Convex Efficiency
58(2)
2.2.4 Weight Space for Convex Efficient Points
60(2)
2.3 Utility Functions
62(13)
2.3.1 Z Utility Theory
62(3)
2.3.2 Nonlinear Utility Functions
65(1)
2.3.3 Additive Utility Functions
66(2)
2.3.4 Additive versus Multiplicative Utility Functions
68(1)
2.3.5 Value Functions for Multicriteria
69(2)
2.3.6 Double Helix (Dual) Value Functions: Prosperity and Mortality
71(2)
2.3.7 Normalized Criteria and Weights
73(2)
2.4 Additive Utility Function: Ordinal/Cardinal Approach
75(18)
2.4.1 Ordinal/Cardinal Approach: I. Assessment of Weights
75(6)
2.4.2 Ordinal/Cardinal Approach: II. External Verification
81(3)
2.4.3 Ordinal/Cardinal Approach: III. Assessment of Qualitative Criteria
84(1)
2.4.4 Ordinal/Cardinal Approach: IV. Ranking of Alternatives
84(1)
2.4.5 Analytic Hierarchy Process
85(2)
2.4.6 Effectiveness of AHP
87(3)
2.4.7 Quasi-linear Double Helix Value and Utility Functions
90(3)
2.5 Multiplicative ZUT
93(7)
2.5.1 Multiplicative ZUT
94(2)
2.5.2 Direct Assessment of M-ZUT
96(3)
2.5.3 Assessment of M-ZUT by Nonlinear Equations
99(1)
2.6 Goal-Seeking ZUT
100(11)
2.6.1 Goal-Seeking ZUT
100(2)
2.6.2 Review of GP and Its Effectiveness
102(3)
2.6.3 Goal Seeking: Z-GP
105(2)
2.6.4 Assessment of Goal-Seeking ZUT
107(2)
2.6.5 Binary Pole ZUT: Goal Seeking/Nadir Avoiding
109(2)
2.7 Multiple Objective Optimization
111(8)
2.7.1 Formulation of Multiple Objective Optimization
112(3)
2.7.2 Generation of Efficient Extreme Alternatives
115(2)
2.7.3 MOO of Additive and Multiplicative Utility Functions
117(2)
2.8 Goal-Seeking Multiple Objective Optimization
119(6)
2.8.1 Generation of Efficient Nonextreme Alternative
119(2)
2.8.2 Goal-Seeking MOO
121(1)
2.8.3 Binary Pole (Goal-Seeking/Nadir-Avoiding) MOO
122(3)
2.9 Paired Comparison and Interactive Methods
125(20)
2.9.1 Paired Comparison: Exhaustive Search
125(1)
2.9.2 Paired Comparison: Basic Idea of Interactive Methods
126(1)
2.9.3 Paired Comparison: Interactive Bicriteria Method
127(3)
2.9.4 Paired Comparison: Advanced Interactive Methods
130(1)
2.9.5 MCDM Validation and Extension to Clustering
130(1)
References
131(3)
Exercises
134(11)
3 Forecasting
145(68)
3.1 Introduction
145(3)
3.1.1 Time Horizons in Time Series Forecasting
147(1)
3.1.2 Principles of Forecasting
147(1)
3.2 Forecasting Approaches
148(10)
3.2.1 Forecasting Process
148(2)
3.2.2 Qualitative-Subjective Forecasting
150(1)
3.2.3 Accuracy Measurement
151(2)
3.2.4 Quality Control and Tracking Error Charts
153(2)
3.2.5 Over- and Underfitting in Forecasting
155(2)
3.2.6 Basics and Types of Time Series
157(1)
3.3 Time Series: Moving Averages
158(3)
3.3.1 Moving Averages
158(2)
3.3.2 Weighted Moving Averages
160(1)
3.4 Time Series: Exponential Smoothing
161(5)
3.4.1 Exponential Smoothing
161(4)
3.4.2 Multicriteria Exponential Smoothing
165(1)
3.5 Time Series: Trend-Based Methods
166(4)
3.5.1 Time Series Trend Analysis by Linear Regression
166(1)
3.5.2 Trend-Adjusted Double-Exponential Smoothing
167(3)
3.6 Time Series: Cyclic/Seasonal
170(4)
3.7 Linear Regression
174(9)
3.7.1 Linear Regression
174(5)
3.7.2 Linear Regression for Time Series
179(2)
3.7.3 Multicriteria Linear Regression
181(2)
3.8 Multiple-Variable Linear Regression
183(5)
3.8.1 Multiple Linear Regression by Quadratic Optimization
183(3)
3.8.2 MSE and Correlation for Multiple Linear Regression
186(2)
3.9 Quadratic Regression
188(8)
3.9.1 Regression by Quadratic Optimization
189(3)
3.9.2 Multiple Variable by Quadratic Optimization
192(3)
3.9.3 Qualitative Regression
195(1)
3.10 Z Theory Nonlinear Regression and Times Series
196(17)
3.10.1 Nonlinear Multiple-Variable Regression by Z Theory
196(3)
3.10.2 Nonlinear Time Series by Z Theory
199(2)
References
201(2)
Exercises
203(10)
4 Aggregate Planning
213(52)
4.1 Introduction
213(2)
4.2 Graphical Approach
215(5)
4.2.1 Input-Output Model
215(2)
4.2.2 Graphical Approach: One Variable
217(3)
4.3 Tabular Method
220(7)
4.4 Linear Programming Method
227(10)
4.4.1 Linear Programming Formulation
227(4)
4.4.2 Integer Linear Programming
231(2)
4.4.3 LP Excel Solver
233(4)
4.5 Integrated LP Aggregate Planning
237(7)
4.5.1 Multiproduct LP Aggregate Planning
237(5)
4.5.2 Multiproduct LP with Common Resources
242(2)
4.5.3 Multicomponent Multiproduct Planning
244(1)
4.6 Multiobjective LP Aggregate Planning
244(8)
4.6.1 LP with Linear Objectives
244(4)
4.6.2 Multicriteria Problem with Nonlinear Objectives
248(4)
4.7 Dissaggregation and Master Schedule
252(13)
References
255(1)
Exercises
256(9)
5 Push-And-Pull (Mrp/Jit) Systems
265(48)
5.1 Introduction
265(2)
5.2 Materials Requirement Planning: Push System
267(5)
5.2.1 Bill of Materials
268(1)
5.2.2 Time-Phased Product Structure
268(1)
5.2.3 Material Requirement Planning
269(3)
5.3 Lot-Sizing Approaches
272(8)
5.3.1 Lot-for-Lot
273(1)
5.3.2 Economic Order Quantity
273(2)
5.3.3 Part Period Balancing
275(1)
5.3.4 Silver-Meal Heuristic
276(2)
5.3.5 Least-Unit-Cost Heuristic
278(1)
5.3.6 Comparison of Lot-Sizing Approaches
279(1)
5.4 Lot Sizing with Capacity Constraints
280(3)
5.4.1 Backward-Forward Lot Sizing
280(2)
5.4.2 Multiple-Item Lot Sizing
282(1)
5.5 Lot-Sizing Optimization
283(11)
5.5.1 Lot-Sizing Optimization with Constraints
283(3)
5.5.2 Bicriteria Push-and-Pull Lot Sizing
286(4)
5.5.3 Multiobjective Optimization (MOO)
290(4)
5.6 Extensions of MRP
294(3)
5.6.1 Closed-Loop MRP
294(1)
5.6.2 Capacity Requirements Planning
295(1)
5.6.3 Manufacturing Resource Planning
295(1)
5.6.4 Enterprise Resource Planning
296(1)
5.6.5 Distribution Resource Planning
296(1)
5.6.6 Supply Chain Management
296(1)
5.7 Just-In-Time: Pull System
297(4)
5.7.1 Principles of JIT
297(3)
5.7.2 Kanban System
300(1)
5.8 Multicriteria Hybrid Push-and-Pull Systems
301(12)
5.8.1 Push-and-Pull Hybrid Systems
302(1)
5.8.2 Three Types of Hybrid Push-and-Pull Systems
303(1)
References
304(2)
Exercises
306(7)
6 Inventory Planning And Control
313(68)
6.1 Introduction
313(4)
6.2 Economic Order Quantity
317(7)
6.2.1 Basic EOQ Model
317(5)
6.2.2 Robustness: Sensitivity of EOQ
322(2)
6.3 Economic Production Quantity
324(3)
6.4 EOQ: Allowing Shortages
327(5)
6.4.1 EOQ Model Allowing Shortages
328(3)
6.4.2 Inventory Model Allowing Limited Shortage
331(1)
6.5 Multicriteria Inventory
332(10)
6.5.1 Bicriteria Economic Order Quantity
332(4)
6.5.2 Bicriteria Economic Production Quantity
336(2)
6.5.3 Tricriteria EOQ Allowing Shortages
338(4)
6.6 Quantity Discount Inventory
342(7)
6.6.1 EOQ with Quantity Discount
342(5)
6.6.2 Bicriteria EOQ with Quantity Discount
347(2)
6.7 Multi-Item Inventory
349(6)
6.7.1 Multi-Item Inventory Optimization
349(2)
6.7.2 Multiobjective Multi-Item Inventory Optimization
351(4)
6.8 Multi-Item Inventory Classification
355(6)
6.8.1 Cost-Based Multi-Item Classification
355(3)
6.8.2 The Critical Index Multi-Item Classification
358(1)
6.8.3 Multicriteria Inventory Classification
359(2)
6.9 Probabilistic Inventory and Safety Stock
361(3)
6.9.1 Basic Model of Probabilistic Inventory
361(2)
6.9.2 Multicriteria Probabilistic Inventory
363(1)
6.10 Single-Period Model: Perishable
364(17)
6.10.1 Target Service Ratio
365(1)
6.10.2 Target Inventory with Continuous Probabilities
366(1)
6.10.3 Target Inventory with Discrete Probabilities
367(1)
6.10.4 Multicriteria of Perishable Inventory
368(2)
References
370(2)
Exercises
372(9)
7 Scheduling And Sequencing
381(58)
7.1 Introduction
381(2)
7.2 Sequencing n Jobs by One Processor
383(12)
7.2.1 Sequencing Performance Measurements
383(1)
7.2.2 Sequencing Algorithms for n x 1
384(5)
7.2.3 Bicriteria Composite Approach for n x 1
389(2)
7.2.4 Generating the Efficient Frontier for n x 1
391(2)
7.2.5 Tricriteria for n x 1
393(2)
7.3 Sequencing n Jobs by Two Processors
395(7)
7.3.1 Flow Shop of n x 2 (Johnson's Rule)
395(2)
7.3.2 Job Shop of n x 2
397(2)
7.3.3 Multicriteria of n x 2
399(3)
7.4 Sequencing n Jobs by m Processors
402(6)
7.4.1 Algorithm for n x 3
402(2)
7.4.2 Algorithm for n x m: Campbell Method
404(2)
7.4.3 Multicriteria of n x m
406(2)
7.5 Job Shop of Two Jobs by m Processors
408(3)
7.5.1 Algorithm for 2 x m
408(2)
7.5.2 Multicriteria of 2 x m
410(1)
7.6 Sequencing of n x m: Head-Tail Approach
411(10)
7.6.1 Overview of Head-Tail for Solving n x m
411(1)
7.6.2 Flow Shop of n x m: Cardinal Head-Tail
412(5)
7.6.3 Job Shop of n x m: Cardinal Head-Tail
417(3)
7.6.4 Multicriteria of n x m
420(1)
7.7 Stochastic Sequencing
421(18)
7.7.1 Stochastic Sequencing of n x 1
422(2)
7.7.2 Bicriteria Stochastic Sequencing of n x 1
424(1)
7.7.3 Stochastic Sequencing of n x 2
425(2)
References
427(2)
Exercises
429(10)
8 Project Management
439(60)
8.1 Introduction
439(2)
8.2 Critical-Path Method
441(11)
8.2.1 Constructing CPM Network
442(4)
8.2.2 Critical-Path Method Algorithm
446(4)
8.2.3 Project Monitoring and Gantt Chart
450(2)
8.3 CPM Time-Cost Trade-Off Method
452(9)
8.3.1 Time-Cost Trade-Off Algorithm
453(3)
8.3.2 Considering Indirect Cost
456(2)
8.3.3 Bicriteria Time-Cost Trade-Off
458(3)
8.4 Linear Programming for Project Management
461(9)
8.4.1 Linear Programming for Solving CPM
461(4)
8.4.2 Linear Programming Time-Cost Trade-Off
465(2)
8.4.3 Multiobjective LP Time-Cost Trade-Off
467(3)
8.5 PERT: Probabilistic CPM
470(9)
8.5.1 PERT Method
470(5)
8.5.2 Bicriteria PERT
475(1)
8.5.3 Tricriteria Time-Cost Trade-Off in PERT
476(3)
8.6 Project Management with Resource Constraints
479(20)
8.6.1 CPM with One Resource Constraint
479(3)
8.6.2 CPM with Multiple-Resource Constraints
482(2)
8.6.3 Bicriteria CPM with Resource Constraints
484(3)
Reference
487(2)
Exercises
489(10)
9 Supply Chain And Transportation
499(48)
9.1 Supply Chain Management
499(5)
9.1.1 Customer and Supplier Interface
501(2)
9.1.2 Supply Chain Performance Criteria
503(1)
9.2 Assignment Problem
504(10)
9.2.1 Hungarian Method
505(2)
9.2.2 Extensions of Assignment Problem
507(3)
9.2.3 Multicriteria Assignment Problem
510(4)
9.3 Optimization for Assignment
514(6)
9.3.1 Integer Linear Programming
514(2)
9.3.2 Multiobjective Optimization of Assignment
516(4)
9.4 Transportation Problem
520(8)
9.4.1 Transportation Problem
520(1)
9.4.2 Minimizing Cost by Vogel's Method
521(4)
9.4.3 Unbalanced Transportation Problem
525(1)
9.4.4 Multicriteria Transportation Problem
526(2)
9.5 Optimization for Transportation
528(19)
9.5.1 Linear Programming for Transportation
528(1)
9.5.2 Multiobjective Optimization of Transportation
529(3)
9.5.3 Transshipment Problem
532(3)
References
535(2)
Exercises
537(10)
10 Productivity And Efficiency
547(32)
10.1 Introduction
547(1)
10.2 Basic Productivity Indexes
548(3)
10.3 Multifactor Productivity Growth
551(2)
10.4 Single-Factor Efficiency
553(2)
10.4.1 Single-Factor Efficiency
553(1)
10.4.2 Bicriteria Single-Factor Efficiency
554(1)
10.5 Multifactor Efficiency and DEA
555(5)
10.5.1 Data Envelopment Analysis
555(1)
10.5.2 Linear Programming Formulation for DEA
556(4)
10.6 Multicriteria Efficiency and DEA
560(4)
10.6.1 Multiobjective Linear Programming of Efficiency and DEA
560(3)
10.6.2 Multicriteria Ranking of Units
563(1)
10.7 Productivity of a Network of Processors
564(15)
10.7.1 Productivity of a Network of Processors
564(4)
10.7.2 Multicriteria Productivity of a Network
568(2)
References
570(1)
Exercises
571(8)
11 Energy System Design And Operation
579(64)
11.1 Introduction
579(4)
11.2 Energy Perspective
583(4)
11.2.1 Climate Change and Global Warming
583(1)
11.2.2 Comparison of Different Types of Energy
584(1)
11.2.3 Environmental Impact
585(1)
11.2.4 Energy Measurement
586(1)
11.3 Multicriteria Energy Decisions
587(4)
11.3.1 Seven Principles for Energy Sustainability
587(1)
11.3.2 Bicriteria Energy Selection
588(1)
11.3.3 Multicriteria Energy Selection
589(2)
11.4 Routing and Procurement in Energy Systems
591(11)
11.4.1 Shortest Route Algorithm
591(6)
11.4.2 Energy Procurement in Distributed Systems
597(1)
11.4.3 Multicriteria Energy Routing
598(4)
11.5 Optimization of Energy Systems
602(17)
11.5.1 Energy Operations Optimization
602(7)
11.5.2 Energy Systems Design Optimization
609(3)
11.5.3 Period-by-Period Optimization
612(1)
11.5.4 Aggregate Multiperiod Optimization
613(3)
11.5.5 Multiobjective Optimization of Energy Systems
616(3)
11.6 Efficiency of Energy Systems
619(3)
11.6.1 Energy Systems with One Input and One Output
620(1)
11.6.2 Energy Systems with Multiple Inputs and Outputs
620(2)
11.7 Case Study: Wind Energy System
622(21)
11.7.1 Wind Energy
622(2)
11.7.2 Wind Power Characteristics
624(3)
11.7.3 Break-Even Analysis
627(3)
References
630(2)
Exercises
632(11)
12 Clustering And Group Technology
643(74)
12.1 Introduction
643(4)
12.2 Clustering Data and Measurements
647(4)
12.2.1 Types of Data Representation
647(2)
12.2.2 Distance Measurement Metrics
649(2)
12.3 Group Technology Clustering
651(4)
12.3.1 Group Technology Problem
651(1)
12.3.2 Classification and Coding
652(1)
12.3.3 Clustering by Visual Inspection and Intuition
653(2)
12.4 Rank Order Clustering
655(9)
12.4.1 ROC Method for Binary Data
655(4)
12.4.2 Bicriteria Rank Order Clustering
659(2)
12.4.3 Selection of Machines to Be Duplicated
661(1)
12.4.4 Tricriteria Rank Order Clustering
661(3)
12.5 Similarity Coefficient-Hierarchical Clustering
664(15)
12.5.1 Similarity Coefficient for Binary Data
664(6)
12.5.2 Simultaneous SC Clustering
670(2)
12.5.3 Multicriteria Similarity Coefficient
672(3)
12.5.4 Linkage Approaches
675(2)
12.5.5 Hierarchical Clustering for Continuous Data
677(2)
12.6 P-Median Optimization Clustering
679(10)
12.6.1 P-Median Method for Binary Data
679(5)
12.6.2 Bicriteria P-Median Clustering
684(3)
12.6.3 P-Median for Continuous Data
687(2)
12.7 K-Means Clustering
689(8)
12.7.1 K-Means Method
689(7)
12.7.2 Bicriteria K-Means
696(1)
12.8 Multiperspective Multicriteria Clustering
697(20)
12.8.1 Multicriteria Clustering Problems
697(1)
12.8.2 Z Theory Clustering Using K-Mean
698(6)
Reference
704(2)
Exercises
706(11)
13 Cellular Layouts And Networks
717(60)
13.1 Introduction
717(4)
13.2 Unidirectional Network Problem
721(3)
13.2.1 Total Flow Based on Product Sequence
721(1)
13.2.2 Total Flow Based on From-To Matrix
722(1)
13.2.3 Concordance and Discordance Measurement
723(1)
13.3 Unidirectional Head-Tail Methods
724(11)
13.3.1 Ordinal (Qualitative) Head-Tail for Unidirectional Flow
724(5)
13.3.2 Cardinal Head-Tail Method for Unidirectional Flow
729(3)
13.3.3 Pairwise Exchange Improvement
732(1)
13.3.4 Multicriteria Unidirectional by Composite Approach
733(2)
13.4 Bidirectional Head-Tail Methods
735(8)
13.4.1 Ordinal (Qualitative) Head-Tail for Bidirectional Flow
737(3)
13.4.2 Cardinal Head-Tail for Bidirectional Flow
740(3)
13.4.3 Multicriteria Bidirectional by Composite Approach
743(1)
13.5 Unidirectional Optimization
743(6)
13.5.1 Optimization Method for Unidirectional Flow
743(4)
13.5.2 Multicriteria Optimization of Unidirectional Flow
747(2)
13.6 Bidirectional Optimization
749(5)
13.6.1 Optimization Method for Bidirectional Flow
749(5)
13.6.2 Multicriteria Optimization for Bidirectional Flow
754(1)
13.7 Combinatorial Optimization By Head-Tail
754(23)
13.7.1 Traveling Salesman Problem: Head-Tail Approach
755(1)
13.7.2 Ordinal (Qualitative) Head-Tail Combinatorial
755(3)
13.7.3 Cardinal Head-Tail Combinatorial
758(2)
13.7.4 Simultaneous Head-Tail Combinatorial
760(2)
13.7.5 Pairwise Exchange Improvement Method
762(1)
13.7.6 Multiobjective Combinatorial Optimization
763(3)
13.7.7 Computational Efficiency of Head-Tail Methods
766(2)
References
768(2)
Exercises
770(7)
14 Assembly Systems
777(26)
14.1 Introduction
777(1)
14.2 Assembly Line Problem
778(1)
14.3 Assembly Line Balancing Methods
779(4)
14.3.1 Largest Candidate Rule
780(1)
14.3.2 Column Precedence
781(1)
14.3.3 Positional Weight Method
782(1)
14.4 Qualitative ALB: Head-Tail Approach
783(3)
14.5 Multicriteria ALB
786(5)
14.5.1 Minimizing Cycle Time for Given Number of Stations
786(1)
14.5.2 Optimizing ALB Profit
787(2)
14.5.3 Bicriteria ALB Problem
789(2)
14.5.4 Tricriteria ALB with Qualitative Closeness
791(1)
14.6 Mixed-Product ALB
791(2)
14.7 Stochastic ALB
793(10)
14.7.1 Single-Objective Stochastic ALB
793(1)
14.7.2 Multicriteria Stochastic ALB
794(1)
Reference
795(2)
Exercises
797(6)
15 Facility Layout
803(58)
15.1 Introduction
803(7)
15.1.1 Layout Classification
805(3)
15.1.2 Hierarchical Layout Planning
808(2)
15.2 Systematic Layout Planning
810(4)
15.3 Rule-Based Layout
814(16)
15.3.1 Calculating Total Cost and Flow
815(1)
15.3.2 Identical Layouts
816(1)
15.3.3 Rule-Based Layout for Single Row
817(2)
15.3.4 Rule-Based Layout for Multiple Rows
819(7)
15.3.5 RBL for Qualitative and Odd Shapes
826(3)
15.3.6 Rule-Based Layout with Constraints
829(1)
15.4 Pairwise Exchange Method
830(6)
15.4.1 Pairwise Exchange Procedure
830(3)
15.4.2 Pairwise Exchange for Qualitative Data
833(2)
15.4.3 Hybrid Rule-Based and Pairwise Exchange
835(1)
15.5 Multicriteria Layout Planning
836(3)
15.5.1 Bicriteria Layout
836(2)
15.5.2 Efficient Frontier
838(1)
15.6 Facility Relayout
839(6)
15.6.1 Calculating Relayout Cost
839(2)
15.6.2 Relayout with Given Budget
841(4)
15.7 Quadratic Assignment Optimization
845(3)
15.8 Layout Software Packages
848(13)
References
849(2)
Exercises
851(10)
16 Location Decisions
861(42)
16.1 Introduction
861(2)
16.2 Break-Even Analysis
863(2)
16.3 Rectilinear Method
865(7)
16.3.1 Rectilinear Method
865(4)
16.3.2 Multicriteria Rectilinear Method
869(3)
16.4 Euclidean Method
872(4)
16.4.1 Center-of-Gravity Method
872(3)
16.4.2 Multicriteria Center-of-Gravity-Method
875(1)
16.5 Multicriteria Location Selection
876(5)
16.5.1 Ordinal/Cardinal Approach for Location Selection
876(3)
16.5.2 Z Theory for Location Selection
879(2)
16.6 Location Allocation-Supplier Selection
881(22)
16.6.1 Single-Objective Location Allocation
881(3)
16.6.2 Multiple-Objective Location Allocation
884(5)
16.6.3 Location Allocation with Capacity Constraints
889(2)
Reference
891(2)
Exercises
893(10)
17 Quality Control And Assurance
903(70)
17.1 Introduction
903(3)
17.2 Multiple-Criteria Quality Function Deployment
906(6)
17.2.1 Three Perspectives of QFD
906(2)
17.2.2 Multicriteria Views of Customer and Producer
908(1)
17.2.3 Multicriteria Views of Customer and Producer
909(3)
17.3 Process Control Background
912(8)
17.3.1 Classification of Types of Measurements
912(3)
17.3.2 Statistical Background
915(5)
17.4 Process Control Variable Charts
920(12)
17.4.1 Control Charts for Variables
920(1)
17.4.2 Mean Chart with Known Standard Deviation
921(2)
17.4.3 Mean Chart with Unknown Standard Deviation
923(3)
17.4.4 Range Chart
926(1)
17.4.5 Sampling Accuracy for Mean Chart
927(2)
17.4.6 Bicriteria Sampling for Mean Chart
929(3)
17.5 Process Control Capability
932(3)
17.5.1 Process Capability Versus Design Tolerances
932(1)
17.5.2 Process Capability for Symmetric Tolerances
932(1)
17.5.3 Process Capability for Nonsymmetric Tolerances
933(1)
17.5.4 Practical Limits on Upper and Lower Control Limits
934(1)
17.6 Process Control Attribute Charts
935(9)
17.6.1 Control Chart for Attributes: p-Chart
936(3)
17.6.2 Control Chart for Attributes: c-Chart
939(2)
17.6.3 Bicriteria Sampling for p-Chart
941(2)
17.6.4 Bicriteria Sampling for c-Chart
943(1)
17.7 Acceptance Sampling Characteristics
944(10)
17.7.1 Statistical Distributions for Sampling
945(3)
17.7.2 Operating Characteristic Curve
948(1)
17.7.3 Producer's and Consumer's Risks
949(3)
17.7.4 Finding Optimal Sampling Size, n, c
952(2)
17.8 Acceptance Sampling Outgoing Quality
954(19)
17.8.1 Average Outgoing Quality
954(2)
17.8.2 Bicriteria Acceptance Sampling
956(3)
17.8.3 Sequential Sampling Plans
959(2)
References
961(2)
Exercises
963(10)
18 Work Measurement
973(36)
18.1 Introduction
973(2)
18.2 Work Analysis
975(2)
18.2.1 Analysis of Methods
975(1)
18.2.2 Study of Motion
976(1)
18.3 Standard Time
977(4)
18.3.1 Stopwatch Studies
977(1)
18.3.2 Standard Time Formulas
978(1)
18.3.3 Standard Time Procedure
979(2)
18.4 Sample Size for Standard Time
981(7)
18.4.1 Finding Sample Size
981(3)
18.4.2 Finding Accuracy of Given Sample Size
984(4)
18.5 Multicriteria Sampling for Standard Time
988(3)
18.5.1 Generation of Set of Efficient Alternatives
988(1)
18.5.2 Ranking with Additive Utility Functions
989(1)
18.5.3 Optimal Sampling Size for Additive Utility Functions
990(1)
18.6 Work Sampling
991(8)
18.6.1 Finding Sample Size for p-Chart
992(1)
18.6.2 Finding Standard Time per Part
993(2)
18.6.3 Illustration of p-Control Charts
995(2)
18.6.4 Multicriteria p-Chart Sampling Plan
997(2)
18.7 Predetermined time standards
999(10)
References
1001(1)
Exercises
1002(7)
19 Reliability And Maintenance
1009(44)
19.1 Introduction
1009(1)
19.2 Reliability of Single Units
1010(6)
19.2.1 Exponential Reliability Functions
1011(3)
19.2.2 Multicriteria Reliability of Single Unit
1014(2)
19.3 Mean Time between Failure
1016(5)
19.3.1 Mean Time between Failure for Single Units
1016(3)
19.3.2 Mean Time between Failure for Multiple Units
1019(1)
19.3.3 Failure Rate Signature
1020(1)
19.4 Reliability of Multiple Units
1021(3)
19.4.1 Series Systems
1021(1)
19.4.2 Parallel Systems
1022(1)
19.4.3 Hybrid Systems
1023(1)
19.5 Multicriteria Reliability of Multiple Units
1024(5)
19.5.1 Reliability-Cost Trade-off Algorithm
1026(1)
19.5.2 Use of Improved Units to Increase System Reliability
1026(3)
19.6 Maintenance Policies
1029(4)
19.6.1 Single-Objective Maintenance Policy
1029(2)
19.6.2 Multiobjective Maintenance Policy
1031(2)
19.7 Replacement Policies
1033(20)
19.7.1 Single-Objective Replacement
1034(1)
19.7.2 Multiobjective Replacement Policy
1035(2)
19.7.3 General Replacement Model
1037(3)
19.7.4 Multicriteria of General Replacement Model
1040(2)
References
1042(2)
Exercises
1044(9)
Appendix A The Standard Normal Distribution 1053(2)
Appendix B Cumulative Binomial Probabilities 1055(2)
Appendix C Cumulative Poisson Probabilities 1057(6)
Index 1063
BEHNAM MALAKOOTI, PHD, PE, is Professor of Systems Engineering in the Electrical Engineering and Computer Science Department of Case Western Reserve University. His current research is in the areas of complex decision making, optimization, and production/manufacturing. He designed intelligent protocols for NASA's space-based networks. He has published over 100 technical journal articles and has consulted with numerous industries and corporations, including General Electric, Parker Hannifin, and BFGoodrich. He is a Fellow of the IEEE, IIE, and SME, and in 1997, he was named Engineer of the Year and also Technical Educator of the Year.