Dedication
Preface
Synopsis of the Contents
Foreword
I. BACKGROUND MATERIAL AND MATHEMATICAL MODELING
1. Introduction
1.1 Main Areas of Manufacturing
1.2.1 Complicating phenomena
1.2.2 Analysis, continuous improvement, and design problems
1.2.3 Fundamental laws of Production Systems Engineering
1.2.4 Techniques used in this textbook
1.3 Summary
1.4 Problems
1.5 Annotated Bibliography
2. Mathematical Tools: Elements of Probability Theory
2.1 Random Events
2.1.1 Terminology
2.1.2 Axioms of probability and their corollaries
2.1.3 Conditional probability
2.1.4 Independence
2.1.5 Total probability formula
2.1.6 Bayes's formula
2.2 Random Variables
2.2.1 Terminology
2.2.2 Discrete random variables
2.2.3 Continuous random variables
2.2.4 Expected value, variance, and coefficient of variation
2.2.5 Vector random variables
2.2.6 Asymptotic properties of sums of random variables
2.3 Random Processes
2.3.1 Terminology
2.3.2 Continuous time, continuous space random processes
2.3.3 Markov processes
2.4 Summary
2.5 Problems
2.6 Annotated Bibliography
3. Mathematical Modeling of Production Systems
3.1 Types of Production Systems
3.1.1 Serial production lines
3.1.2 Assembly systems
3.2 Structural Modeling
3.3.1 Timing issues
3.3.2 Machine reliability models
3.3.3 Notations
3.3.4 Machine model identification
3.3.5 Calculating parameters of aggregated machines
3.3.6 Machine quality models
3.4 Mathematical Models of Buffers
3.4.1 Modeling
3.4.2 Buffer parameters identification
3.5.1 Slotted time case
3.5.2 Continuous time case
3.6 Performance Measures
3.6.1 Production rate and throughput
3.6.2 Work-in-process and finished goods inventory
3.6.3 Probabilities of blockages and starvations
3.6.4 Due-time performance
3.6.5 Transient characteristics
3.6.6 Evaluating performance measures on the factory floor
3.7 Model Validation
3.8.1 Modeling
3.9 Simplification: Transforming Exponential Models into Bernoulli Ones
3.9.1 Motivation
3.9.3 The exp-B transformation
3.9.4 The B-exp transformation
3.9.5 Exp-B and B-exp transformations for assembly systems
3.10 Case Studies
3.10.1 Automotive ignition coil processing system
3.10.2 Automotive paint shop production system
3.10.3 Automotive ignition module assembly system
3.11 Summary
3.12 Problems
3.13 Annotated Bibliography
II. SERIAL PRODUCTION LINES WITH BERNOULLI MODEL OF MACHINE RELIABILITY
4. Analysis of Bernoulli Lines
4.1 Two-machine Lines
4.1.1 Mathematical description
4.1.2 Steady state probabilities
4.1.3 Formulas for the performance measures
4.1.4 Asymptotic properties
4.2 M > 2-machineLines
4.2.1 Mathematical description and approach
4.2.2 Aggregation procedure and its properties
4.2.3 Formulas for the performance measures
4.2.4 Asymptotic properties of M > 2-machine lines
4.2.5 Accuracy of the estimates
4.3 System-Theoretic Properties
4.3.1 Static laws of production systems
4.3.2 Reversibility
4.3.3 Monotonicity
4.4 Case Studies
4.4.1 Automotive ignition coil processing system
4.4.2 Automotive paint shop production system
4.5 Summary
4.6 Problems
4.7 Annotated Bibliography
5. Continuous Improvement of Bernoulli Lines
5.1 Constrained Improvability
5.1.1 Resource constraints and definitions
5.1.2 Improvability with respect to WF
5.1.3 Improvability with respect to WF and BC simultaneously
5.1.4 Improvability with respect to BC
5.2 Unconstrained Improvability
5.2.1 Definitions
5.2.2 Identification of bottlenecks in two-machine lines
5.2.3 Identification of bottlenecks in M > 2-machine lines
5.2.4 Potency of buffering
5.2.5 Designing continuous improvement projects
5.4 Case Studies
5.4.2 Automotive paint shop production system
5.5 Summary
5.6 Problems
5.7 Annotated Bibliography
6. Design of Lean Bernoulli Lines
6.2 Lean Buffering in Bernoulli Lines with Identical Machines
6.2.1 Two-machine lines
6.2.2 Three-machine lines
6.2.3 M > 3-machine lines
6.3 Lean Buffering in Serial Lines with Non-identical Bernoulli Machines
6.3.1 Two-machine lines
6.3.2 M > 2-machine lines
6.4 Case Studies
6.4.1 Automotive ignition coil processing system
6.4.2 Automotive paint shop production system
6.5 Summary
6.6 Problems
6.7 Annotated Bibliography
7. Closed Bernoulli Lines
7.1.1 Model
7.1.2 Problems addressed
7.2.1 Two-machine lines
7.2.2 M > 2-machine lines
7.3 Improvability
7.3.1 Two-machine lines
7.3.2 M > 2-machine lines
7.3.3 Comparisons
7.4 Bottleneck Identification
7.4.1 Two-machine lines
7.4.2 M > 2-machinelines
7.5 Leanness
7.6 Case Study
7.6.1 Modeling and model validation of closed automotive paint shop production system
7.6.2 S-improvability
7.6.3 Lean system design
7.7 Summary
7.8 Problems
7.9 Annotated Bibliography
8. Product Quality in Bernoulli Lines
8.1.1 Model and problem formulation
8.1.2 Performance analysis
8.1.3 Bottlenecks
8.1.4 Design
8.2 Bernoulli Lines with Quality-Quantity Coupling Machines
8.2.1 Model and problem formulation
8.2.2 Monotonicity properties
8.2.3 Bottlenecks
8.3 Bernoulli Lines with Rework
8.3.1 Model and problem formulation
8.3.2 Performance analysis
8.3.3 Bottleneck identification
8.4 Summary
8.5 Problems
8.6 Annotated Bibliography
9. Customer Demand Satisfaction in Bernoulli Lines
9.1 Modeling and Parametrization
9.1.1 Production-inventory-customer (PIC) model
9.1.2 Due-time performance measure
9.1.3 Parametrization
9.2 Analysis of DTP
9.2.1 Evaluating DTP in PIC systems with one-machine PS
9.2.2 Evaluating DTP in PIC systems with M-machine PS
9.3 Design of Lean FGB for Desired DTP
9.3.1 Lean FGB
9.3.2 Conservation of filtering
9.4 Analysis of DTP for Random Demand
9.4.1 Random demand modeling
9.4.2 Evaluating DTP for random demand
9.4.3 DTP degradation as a function of demand variability
9.4.4 Dependence of DTP on the shape of demand pmf's
9.5 Case Study
9.6 Summary
9.7 Problems
9.8 Annotated Bibliography
10. Transient Behavior of Bernoulli Lines
10.1 Problem Formulation
10.1.1 Mathematical description
10.1.2 Second largest eigenvalue problem
10.1.3 Pre-exponential factor problem
10.1.4 Settling time problem
10.1.5 Production losses problem
10.2 Analysis of the Second Largest Eigenvalue
10.2.1 Two-machine lines
10.2.2 Three-machine lines
10.3 Analysis of the Pre-exponential Factors
10.4 Analysis of the Settling Time
10.4.1 Behavior of PR(n) and WIP(n)
10.4.2 Analysis of tsPR and tsWIP
10.5 Analysis of the Production Losses
10.5.1 Approach
10.5.2 Percent of loss when the buffers are empty at the beginning of the shift
10.5.3 Percent of loss when the buffers are not empty at the beginning of the shift
10.6 Summary
10.7 Problems
10.8 Annotated Bibliography
III. SERIAL PRODUCTION LINES WITH CONTINUOUS TIME MODELS OF MACHINE RELIABILITY
11. Analysis of Exponential Lines
11.1 Synchronous Exponential Lines
11.1.1 Two-machine case
11.1.2 M > 2-machine case
11.2 Asynchronous Exponential Lines
11.2.1 Two-machine case
11.2.2 M > 2-machinecase
11.3 Case Studies
11.3.1 Automotive ignition coil processing system
11.3.2 Crank shaft production line
11.4 Summary
11.5 Problems
11.6 Annotated Bibliography
12. Analysis of Non-Exponential Lines
12.1 Systems Considered
12.1.1 Mathematical description
12.1.2 Second-order-similar production lines
12.2 Sensitivity of PR and TP to Machine Reliability Model
12.3 Empirical Formulas for PR and TP
12.4 Summary
12.5 Problems
12.6 Annotated Bibliography
13. Improvement of Continuous Lines
13.1 Constrained Improvability
13.1.1 Resource constraints and definitions
13.1.2 Improvability with respect to CT
13.1.3 Improvability with respect to BC
13.2 Unconstrained Improvability
13.2.1 Definitions
13.2.2 One-machine lines
13.2.3 Two-machine synchronous exponential lines
13.2.4 Asynchronous exponential lines
13.2.5 M ≥ 2-machine non-exponential lines
13.2.6 Buffering potency and measurement-based management
13.3 Case Study
13.4 Summary
13.5 Problems
13.6 Annotated Bibliography
14. Design of Lean Continuous Lines
14.1 Parametrization and Problem Formulation
14.2 Lean Buffering in Synchronous Lines with Identical Exponential Machines
14.2.1 Two-machine lines
14.2.2Three-machinelines
14.2.3 M > 3-machinelines
14.3 Lean Buffering in Synchronous Lines with Non-identical Exponential Machines
14.3.1 Two-machine lines
14.3.2 A special class of three-machine lines
14.3.3 M > 2-machinelines
14.4 Lean Buffering in Synchronous Lines with Non-exponential Machines
14.4.1 Approach
14.4.2 Sensitivity of kE to machine reliability models
14.4.3 Empirical formulas for kE
14.5 Summary
14.6 Problems
14.7 Annotated Bibliography
15. Customer Demand Satisfaction in Continuous Lines
15.1 Modeling and Parametrization
15.1.1 Production-inventory-customer (PIC) system
15.1.2 DTP Definition
15.1.3 Parametrization
15.2 DTP Evaluation in PIC Systems with Exponential Machines
15.2.1 DTP in PIC systems with one-machine PS
15.2.2 DTP in PIC systems with M-machine PS
15.3 Lean FGB and Conservation of Filtering in PIC Systems with Exponential Machines
15.3.1 Lean FGB
15.3.2 Typical behavior of νDTP vs. τ
15.4 DTP in the Case of Random Demand
15.4.1 Random demand modeling
15.4.2 DTP for random demand in PIC systems with exponential machines
15.4.3 DTP degradation as a function of demand variability
15.4.4 Dependence of DTP on the shape of demand pmf
15.5 Summary
15.6 Problems
15.7 Annotated Bibliography
IV. ASSEMBLY SYSTEMS
16. Assembly Systems with Bernoulli Model of Machine Reliability
16.1 Analysis of Bernoulli Assembly Systems
16.1.1 Three-machine assembly systems
16.1.2 M > 3-machine assembly systems
16.2 Continuous Improvement of Bernoulli Assembly Systems
16.2.1 Constrained improvability
16.2.2 Unconstrained improvability
16.3 Design of Lean Bernoulli Assembly Systems
16.4 Customer Demand Satisfaction in Bernoulli Assembly Systems
16.5 Case Studies
16.5.1 Automotive ignition module assembly system
16.5.2 Injection molding assembly system
16.6 Summary
16.7 Problems
16.8 Annotated Bibliography
17. Assembly Systems with Continuous Time Models of Machine Reliability
17.1 Analysis of Assembly Systems with Exponential Machines
17.1.1 Systems addressed
17.1.2 Synchronous case
17.1.3 Asynchronous case
17.2 Analysis of Non-exponential Assembly Systems
17.3 Improvement of Assembly Systems with Continuous Time Models of Machine Reliability
17.3.1 Constrained improvability
17.3.2 Unconstrained improvability
17.4 Design on Lean Assembly Systems with Continuous Machines
17.5 Customer Demand Satisfaction in Assembly Systems with Continuous Machines
17.6 Case Studies
17.7 Summary
17.8 Problems
17.9 Annotated Bibliography
V. SUMMARY, PSE TOOLBOX, AND PROOFS
18. Summary of Main Facts of Production Systems Engineering
18.1 Individual Machines
18.2 Serial Lines
18.2.1 Performance analysis
18.2.2 Continuous improvement
18.2.3 Design
18.3 Assembly Systems
19. PSE Toolbox
19.1 Architecture and Functions
19.2 Modeling Function
19.2.1 Aggregation of parallel machines
19.2.2 Aggregation of consecutive dependent machines
19.2.3 Exp-B transformation for serial lines
19.2.4 B-exp transformation for serial lines
19.2.5 Exp-B transformation for assembly systems
19.2.6 B-exp transformation for serial lines
19.3 Performance Analysis Function
19.3.1 Analysis of serial lines with Bernoulli machines
19.3.2 Analysis of synchronous serial lines with exponential machines
19.3.3 Analysis of asynchronous serial lines with exponential machines
19.3.4 Analysis of closed lines with Bernoulli machines
19.3.5 Analysis of assembly systems with Bernoulli machines
19.4 Continuous Improvement Function
19.4.1 Unimprovable allocation of WF in Bernoulli serial lines
19.4.2 Unimprovable allocation of WF and BC simultaneously in Bernoulli serial lines
19.4.3 WF-continuous improvement procedure for Bernoulli serial lines
19.4.4 BC-continuous improvement procedure for Bernoulli serial lines
19.4.5 S-continuous improvement procedure for closed Bernoulli lines
19.5 Bottleneck Identification Function
19.5.1 BN-m and BN-b in serial lines with Bernoulli machines
19.5.2 c-BN and BN-b in serial lines with exponential machines
19.5.3 c-BN and BN-b in serial lines with general model of machine reliability
19.5.4 BN-m and BN-b in closed lines with Bernoulli machines
19.6 Lean Buffer Design Function
19.6.1 Lean buffering for serial lines with identical Bernoulli machines
19.6.2 Lean buffering for serial lines with non-identical Bernoulli machines
19.7 Product Quality Function
19.7.1 Analysis of Bernoulli lines with non-perfect quality machines and inspection operations
19.8 Customer Demand Satisfaction Function
19.8.1 DTP in PIC system with one Bernoulli machine
19.9 Simulation Function
19.9.1 Simulation of serial lines with Bernoulli machines
19.9.2 Simulation of serial lines with exponential machines
19.9.3 Simulation of serial lines with general model of machine reliability
20. Proofs
20.1Proofs for Part II
20.1.1 Proofs for Chapter 4
20.1.2 Proofs for Chapter 5
20.1.3 Proofs for Chapter 6
20.1.4 Proofs for Chapter 7
20.1.5 Proofs for Chapter 8
20.1.6 Proofs for Chapter 10
20.2 Proofs for Part III
20.2.1 Proofs for Chapter 12
20.3 Proofs for Part IV
Epilogue