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El. knyga: Inventory and Production Management in Supply Chains

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(Pennsylvania State University), (University of San Diego, California, USA), (University of Calgary, Alberta, Canada)
  • Formatas: 810 pages
  • Išleidimo metai: 19-Dec-2016
  • Leidėjas: CRC Press Inc
  • ISBN-13: 9781315356808
Kitos knygos pagal šią temą:
Inventory and Production Management in Supply ChainsDidesnis paveikslėlis
  • Formatas: 810 pages
  • Išleidimo metai: 19-Dec-2016
  • Leidėjas: CRC Press Inc
  • ISBN-13: 9781315356808
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Authored by a team of experts, the new edition of this bestseller presents practical techniques for managing inventory and production throughout supply chains. It covers the current context of inventory and production management, replenishment systems for managing individual inventories within a firm, managing inventory in multiple locations and firms, and production management. The book presents sophisticated concepts and solutions with an eye towards today’s economy of global demand, cost-saving, and rapid cycles. It explains how to decrease working capital and how to deal with coordinating chains across boundaries.

Preface xix
Acknowledgments xxiii
Authors xxv
Section I The Context And Importance Of Inventory Management And Production Planning
1 The Importance of Inventory Management and Production Planning and Scheduling
3(20)
1.1 Why Aggregate Inventory Investment Fluctuates: The Business Cycle
7(1)
1.2 Corporate Strategy and the Role of Top Management
8(2)
1.3 The Relationship of Finance and Marketing to Inventory Management and Production Planning and Scheduling
10(2)
1.3.1 Finance
10(1)
1.3.2 Marketing
11(1)
1.4 Operations Strategy
12(5)
1.4.1 Mission
13(1)
1.4.2 Objectives
13(2)
1.4.3 Management Levers
15(1)
1.4.4 General Comments
16(1)
1.5 Measures of Effectiveness for Inventory Management and Production Planning and Scheduling Decisions
17(1)
1.6 Summary
18(1)
Problems
18(2)
References
20(3)
2 Frameworks for Inventory Management and Production Planning and Scheduling
23(50)
2.1 The Diversity of Stock-Keeping Units
23(1)
2.2 The Bounded Rationality of a Human Being
24(1)
2.3 Decision Aids for Managing Diverse Individual Items
25(1)
2.3.1 Conceptual Aids
25(1)
2.3.2 Physical Aids
25(1)
2.4 Frameworks for Inventory Management
26(5)
2.4.1 Functional Classifications of Inventories
26(2)
2.4.2 The A-B-C Classification as a Basis for Designing Individual Item Decision Models
28(3)
2.5 A Framework for Production Planning and Scheduling
31(9)
2.5.1 A Key Marketing Concept: The Product Life Cyde
31(2)
2.5.2 Different Types of Production Processes
33(4)
2.5.3 The Product-Process Matrix
37(3)
2.6 Costs and Other Important Factors
40(6)
2.6.1 Cost Factors
40(4)
2.6.2 Other Key Variables
44(2)
2.7 Three Types of Modeling Strategies
46(1)
2.7.1 Detailed Modeling and Analytic Selection of the Values of a Limited Number of Decision Variables
47(1)
2.7.2 Broader-Scope Modeling with Less Optimization
47(1)
2.7.3 Minimization of Inventories with Little Modeling
47(1)
2.8 The Art of Modeling
47(2)
2.9 Explicit Measurement of Costs
49(3)
2.10 Implicit Cost Measurement and Exchange Curves
52(1)
2.11 The Phases of a Major Study of an Inventory Management or Production Planning and Scheduling System
53(8)
2.11.1 Consideration
54(1)
2.11.2 Analysis
55(2)
2.11.3 Synthesis
57(1)
2.11.4 Choosing among Alternatives
57(1)
2.11.5 Control
58(1)
2.11.6 Evaluation
58(1)
2.11.7 General Comments
58(1)
2.11.8 Transient Effects
59(1)
2.11.9 Physical Stock Counts
59(2)
2.12 Summary
61(1)
Problems
61(7)
Appendix 2A: The Lognormal Distribution
68(2)
References
70(3)
3 Forecasting Models and Techniques
73(72)
3.1 The Components of Time-Series Analysis
75(2)
3.2 The Three Steps Involved in Statistically Forecasting a Time Series
77(1)
3.3 Some Aggregate Medium-Range Forecasting Methods
78(3)
3.3.1 Regression Procedures
79(2)
3.4 Individual-Item, Short-Term Forecasting: Models and Procedures
81(23)
3.4.1 The Simple Moving Average
82(2)
3.4.2 Simple Exponential Smoothing
84(4)
3.4.3 Exponential Smoothing for a Trend Model
88(4)
3.4.4 Winters Exponential Smoothing Procedure for a Seasonal Model
92(9)
3.4.5 Selection of Smoothing Constants
101(3)
3.5 Measuring the Performance of a Forecasting Process
104(13)
3.5.1 Measures of Forecast Accuracy
105(4)
3.5.2 Estimating the Standard Deviation of Forecast Errors over a Lead Time
109(2)
3.5.3 Monitoring Bias
111(4)
3.5.4 Corrective Actions in Statistical Forecasting
115(2)
3.5.5 Probability Distributions of Forecast Errors
117(1)
3.6 Handling Anomalous Demand
117(1)
3.7 Incorporation of Human Judgment
118(2)
3.7.1 Factors Where Judgment Input Is Needed
118(1)
3.7.2 Guidelines for the Input and Monitoring of Judgment
119(1)
3.8 Dealing with Special Classes of Individual Items
120(5)
3.8.1 Items with Limited History
120(2)
3.8.2 Intermittent and Erratic Demand
122(1)
3.8.3 Replacement or Service Parts
123(1)
3.8.4 Terminal Demand
124(1)
3.9 Assessing Forecasting Procedures: Tactics and Strategy
125(3)
3.9.1 Statistical Accuracy of Forecasts
125(1)
3.9.2 Some Issues of a More Strategic Nature
126(2)
Problems
128(7)
Appendix 3A: Derivations
135(2)
References
137(8)
Section II Replenishment Systems For Managing Individual Item Inventories Within A Firm
4 Order Quantities When Demand Is Approximately Level
145(54)
4.1 Assumptions Leading to the Basic EOQ
146(1)
4.2 Derivation of the EOQ
147(5)
4.2.1 Numerical Illustration
151(1)
4.3 Sensitivity Analysis
152(2)
4.4 Implementation Aids
154(1)
4.4.1 Numerical Illustration
155(1)
4.5 Quantity Discounts
155(5)
4.5.1 Numerical Illustrations
158(1)
4.5.2 Item A (An Illustration of Case a of Figure 4.5)
159(1)
4.5.3 Item B (An Illustration of Case b of Figure 4.5)
159(1)
4.5.4 Item C (An Illustration of Case c of Figure 4.5)
160(1)
4.6 Accounting for inflation
160(4)
4.6.1 Price Established Independent of Ordering Policy
161(2)
4.6.2 Price Set as a Fixed Fractional Markup on Unit Variable Cost
163(1)
4.7 Limits on order sizes
164(2)
4.7.1 Maximum Time Supply or Capacity Restriction
164(1)
4.7.2 Minimum Order Quantity
165(1)
4.7.3 Discrete Units
165(1)
4.8 Finite Replenishment Rate: The Economic Production Quantity
166(2)
4.9 Incorporation of Other Factors
168(8)
4.9.1 Nonzero Constant Lead Time That Is Known with Certainty
168(1)
4.9.2 Nonzero Payment Period
169(1)
4.9.3 Different Types of Carrying Charge
169(1)
4.9.4 Multiple Setup Costs: Freight Discounts
170(2)
4.9.5 A Special Opportunity to Procure
172(4)
4.10 Selection of the Carrying Charge (r), the Fixed Cost per Replenishment (A) , or the Ratio A/r Based on Aggregate Considerations: The Exchange Curve
176(3)
4.10.1 Exchange Curve Illustration
177(2)
4.11 Summary
179(1)
Problems
179(8)
Appendix 4A: Derivations
187(6)
References
193(6)
5 Lot Sizing for Individual Items with Time-Varying Demand
199(38)
5.1 The Complexity of Time-Varying Demand
200(1)
5.2 The Choice of Approaches
201(1)
5.3 General Assumptions and a Numerical Example
202(2)
5.3.1 The Assumptions
202(1)
5.3.2 A Numerical Example
203(1)
5.4 Use of a Fixed EOQ
204(1)
5.5 The Wagner-Whitin Method: An "Optimal" Solution under an Additional Assumption
205(7)
5.5.1 The Algorithm
206(3)
5.5.2 Potential Drawbacks of the Algorithm
209(3)
5.6 Heuristic Approaches for a Significantly Variable Demand Pattern
212(9)
5.6.1 The Silver—Meal, or Least Period Cost, Heuristic
212(4)
5.6.2 The EOQ Expressed as a Time Supply (POQ)
216(1)
5.6.3 Lot-for-Lot
216(1)
5.6.4 Least Unit Cost
216(1)
5.6.5 Part-Period Balancing
216(2)
5.6.6 Performance of the Heuristics
218(1)
5.6.7 When to Use Heuristics
219(1)
5.6.8 Sensitivity to Errors in Parameters
220(1)
5.6.9 Reducing System Nervousness
221(1)
5.7 Handling of Quantity Discounts
221(2)
5.8 Aggregate Exchange Curves
223(1)
5.9 Summary
223(1)
Problems
223(9)
Appendix 5A: Dynamic Programming and Linear Programming Formulations
232(1)
References
233(4)
6 Individual Items with Probabilistic Demand
237(82)
6.1 Some Important Issues and Terminology
238(2)
6.1.1 Different Definitions of Stock Level
238(1)
6.1.2 Backorders versus Lost Sales
239(1)
6.1.3 Three Key Issues to Be Resolved by a Control System under Probabilistic Demand
239(1)
6.2 The Importance of the Item: A, B, and C Classification
240(1)
6.3 Continuous versus Periodic Review
240(1)
6.4 The Form of the Inventory Policy: Four Types of Control Systems
241(4)
6.4.1 Order-Point, Order-Quantity (s, Q) System
242(1)
6.4.2 Order-Point, Order-Up-to-Level (s, S) System
242(1)
6.4.3 Periodic-Review, Order-Up-to-Level (R, S) System
243(1)
6.4.4 (R, s, S) System
244(1)
6.5 Specific Cost and Service Objectives
245(5)
6.5.1 Choosing the Best Approach
246(1)
6.5.2 SSs Established through the Use of a Simple-Minded Approach
246(2)
6.5.3 SSs Based on Minimizing Cost
248(1)
6.5.4 SSs Based on Customer Service
248(2)
6.5.5 SSs Based on Aggregate Considerations
250(1)
6.6 Two Examples of Finding the Reorder Point s in a Continuous-Review, Order-Point, Order-Quantity (s, Q) System
250(6)
6.6.1 Protection over the Replenishment Lead Time
251(1)
6.6.2 An Example Using a Discrete Distribution
252(4)
6.7 Decision Rules for Continuous-Review, Order-Point, Order-Quantity (s, Q) Control Systems
256(21)
6.7.1 Common Assumptions and Notation
257(2)
6.7.2 General Approach to Establishing the Value of s
259(1)
6.7.3 Common Derivation
260(3)
6.7.4 Decision Rule for a Specified Safety Factor (k)
263(1)
6.7.5 Decision Rule for a Specified Cost (B1) per Stockout Occasion
263(3)
6.7.6 Decision Rule for a Specified Fractional Charge (B2) per Unit Short
266(2)
6.7.7 Decision Rule for a Specified Fractional Charge (B3) per Unit Short per Unit Time
268(1)
6.7.8 Decision Rule for a Specified Charge (B4) per Customer Line Item Short
269(1)
6.7.9 Decision Rule for a Specified Probability (P1) of No Stockout per Replenishment Cycle
269(2)
6.7.10 Decision Rule for a Specified Fraction (P2) of Demand Satisfied Directly from Shelf
271(2)
6.7.11 Decision Rule for a Specified Average Time (TBS) between Stockout Occasions
273(1)
6.7.12 Decision Rule for the Allocation of a TSS to Minimize the ETSOPY
274(1)
6.7.13 Decision Rule for the Allocation of a TSS to Minimize the ETVSPY
274(1)
6.7.14 Nonnormal Lead Time Demand Distributions
275(2)
6.8 Implied Costs and Performance Measures
277(1)
6.9 Decision Rules for Periodic-Review, Order-Up-to-Level (R, S) Control Systems
277(5)
6.9.1 The Review Interval (R)
278(1)
6.9.2 The Order-Up-to-Level (5)
278(2)
6.9.3 Common Assumptions and Notation
280(1)
6.9.4 Common Derivation
280(2)
6.10 Variability in the Replenishment Lead Time Itself
282(4)
6.10.1 Approach 1: Use of the Total Demand over the Full Lead Time
283(1)
6.10.2 Approach 2: Use of the Distribution of Demand Rate per Unit Time Combined with the Lead Time Distribution
284(1)
6.10.3 Nonnormal Distributions
285(1)
6.11 Exchange Curves Involving SSs for (s, Q) Systems
286(8)
6.11.1 Single Item Exchange Curve: Inventory versus Service
287(1)
6.11.2 An Illustration of the Impact of Moving Away from Setting Reorder Points as Equal Time Supplies
288(2)
6.11.3 Derivation of the SS Exchange Curves
290(3)
6.11.4 Composite Exchange Curves
293(1)
6.12 Summary
294(1)
Problems
295(9)
Appendix 6A: Some Illustrative Derivations and Approximations
304(8)
References
312(7)
Section III Special Classes Of Items
7 Managing the Most Important Inventories
319(32)
7.1 Nature of Class A Items
319(1)
7.2 Guidelines for Control of A Items
320(2)
7.3 Simultaneous Determination of s and Q for Fast-Moving Items
322(5)
7.3.1 Decision Rules
323(2)
7.3.2 Cost Penalties
325(1)
7.3.3 Further Comments
325(2)
7.4 Decision Rules for (s, S) Systems
327(5)
7.4.1 Simple Sequential Determination of s and S
328(1)
7.4.2 Simultaneous Selection of s and S Using the Undershoot Distribution
328(3)
7.4.3 Comparison of the Methods
331(1)
7.5 Decision Rules for (R, s, S) Systems
332(5)
7.5.1 Decision Rule for a Specified Fractional Charge (B3) per Unit Short at the End of Each Period
332(2)
7.5.2 Decision Rule for a Specified Fraction (P2) of Demand Satisfied Directly from Shelf
334(3)
7.6 Coping with Nonstationary Demand
337(2)
7.7 Comments on Multiple Sources of Supply and Expediting
339(2)
7.8 Summary
341(1)
Problems
341(4)
Appendix 7A: Simultaneous Solutions for Two Control Parameters
345(1)
References
346(5)
8 Managing Slow-Moving and Low-Value (Class C) Inventories
351(36)
8.1 Order-Point, Order-Quantity (s, Q) Systems for Slow-Moving A Items
351(6)
8.1.1 B2 Cost Measure for Very-Slow-Moving, Expensive Items (Q = 1)
353(3)
8.1.2 Case of Q greater than or equal to 1 and a B1 Cost Structure
356(1)
8.1.3 Simultaneous Determination of s and Q for Slow-Moving Items
356(1)
8.2 Controlling the Inventories of Intermittent Demand Items
357(1)
8.3 Nature of C Items
358(1)
8.4 Control of C Items Having Steady Demand
359(4)
8.4.1 Inventory Records
359(1)
8.4.2 Selecting the Reorder Quantity (or Reorder Interval)
359(1)
8.4.3 Selecting the Reorder Point (or Order-up-to Level)
360(1)
8.4.4 Two-Bin System Revisited
361(1)
8.4.5 Simple Form of the (R, S) System
362(1)
8.4.6 Grouping of Items
363(1)
8.5 Control of Items with Declining Demand Patterns
363(2)
8.5.1 Establishing the Timing and Sizes of Replenishments under Deterministic Demand
363(1)
8.5.2 Sizing of the Final Replenishment under Probabilistic Demand
364(1)
8.6 Reducing Excess Inventories
365(6)
8.6.1 Review of the Distribution by Value
366(2)
8.6.2 Rule for the Disposal Decision
368(2)
8.6.3 Options for Disposing of Excess Stock
370(1)
8.7 Stocking versus Not Stocking an Item
371(3)
8.7.1 Relevant Factors
371(1)
8.7.2 Simple Decision Rule
372(1)
8.7.3 Some Extensions
373(1)
8.8 Summary
374(1)
Problems
374(5)
Appendix 8A: Poisson Distribution and Some Derivations
379(5)
References
384(3)
9 Style Goods and Perishable Items
387(50)
9.1 Style Goods Problem
388(1)
9.2 Simplest Case: Unconstrained, Single-Item, Newsvendor Problem
389(8)
9.2.1 Determination of the Order Quantity by Marginal Analysis
389(2)
9.2.2 An Equivalent Result Obtained through Profit Maximization
391(1)
9.2.3 Case of Normally Distributed Demand
392(2)
9.2.4 Case of a Fixed Charge to Place the Order
394(1)
9.2.5 Case of Discrete Demand
395(2)
9.3 Single-Period, Constrained, Multi-Item Situation
397(4)
9.3.1 Numerical Illustration
399(2)
9.4 Postponed Product Differentiation
401(7)
9.4.1 Value of Delayed Financial Commitment
402(1)
9.4.2 Value of Flexibility
403(5)
9.5 More than One Period in Which to Prepare for the Selling Season
408(1)
9.6 Multiperiod Newsvendor Problem
408(1)
9.7 Other Issues Relevant to the Control of Style Goods
409(4)
9.7.1 Updating of Forecasts
409(1)
9.7.2 Reorders and Markdowns
410(1)
9.7.3 Reserving Capacity Ahead of Time
411(1)
9.7.4 Inventory Policies for Common Components
411(1)
9.7.5 Other Research
412(1)
9.8 Inventory Control of Perishable Items
413(1)
9.9 Summary
414(1)
Problems
414(8)
Appendix 9A: Derivations
422(5)
References
427(10)
Section IV Managing Inventory Across Multiple Locations And Multiple Firms
10 Coordinated Replenishments at a Single Stocking Point
437(50)
10.1 Advantages and Disadvantages of Coordination
438(1)
10.2 Deterministic Case: Selection of Replenishment Quantities in a Family of Items
439(4)
10.2.1 Assumptions
439(1)
10.2.2 Decision Rule
440(3)
10.2.3 A Bound on the Cost Penalty of the Heuristic Solution
443(1)
10.3 Deterministic Case with Group Discounts
443(4)
10.3.1 Numerical Illustration
446(1)
10.4 Case of Probabilistic Demand and No Quantity Discounts
447(4)
10.4.1 (S, c, s), or Can-Order, Systems
448(1)
10.4.2 Periodic Review System
448(3)
10.5 Probabilistic Demand and Quantity Discounts
451(5)
10.5.1 A Full Truckload Application
453(1)
10.5.2 Numerical Illustration
454(2)
10.6 Production Environment
456(8)
10.6.1 Case of Constant Demand and Capacity: Economic Lot Scheduling Problem
456(5)
10.6.2 Case of Time-Varying Demand and Capacity: Capacitated Lot Sizing
461(2)
10.6.3 Probabilistic Demand: The Stochastic Economic Lot Scheduling Problem
463(1)
10.7 Shipping Consolidation
464(1)
10.8 Summary
465(1)
Problems
465(9)
Appendix 10A: Derivation of Results in Section 10.2
474(3)
References
477(10)
11 Multiechelon Inventory Management
487(56)
11.1 Multiechelon Inventory Management
487(2)
11.2 Structure and Coordination
489(2)
11.3 Deterministic Demand
491(7)
11.3.1 Sequential Stocking Points with Level Demand
491(4)
11.3.2 Other Results for the Case of Level Demand
495(1)
11.3.3 Multiechelon Stocking Points with Time-Varying Demand
496(2)
11.4 Probabilistic Demand
498(15)
11.4.1 Base Stock Control System
501(2)
11.4.2 Serial Situation
503(3)
11.4.3 Arborescent Situation
506(7)
11.5 Remanufacturing and Product Recovery
513(10)
11.5.1 Multiechelon Situation with Probabilistic Usage and One-for-One Ordering
515(5)
11.5.2 Some Extensions of the Multiechelon Repair Situation
520(1)
11.5.3 Some Insights and Results for the More General Context of Remanufacturing and Product Recovery
521(2)
11.6 Additional Insights
523(3)
11.6.1 Economic Incentives to Centralize Stocks
523(2)
11.6.2 Where to Deploy Stock
525(1)
11.6.3 Lateral Transshipments
526(1)
11.7 Summary
526(1)
Problems
526(4)
Appendix 11A: Derivation of the Logic for Computing the Best Replenishment Quantities in a Deterministic, Two-Stage Process
530(1)
References
531(12)
12 Coordinating Inventory Management in the Supply Chain
543(18)
12.1 Information Distortion in a Supply Chain
544(2)
12.2 Collaboration and Information Sharing
546(2)
12.2.1 Sales and Operations Planning
546(1)
12.2.2 Collaborative Forecasting
547(1)
12.3 Vendor-Managed Inventory
548(1)
12.4 Aligning Incentives
548(7)
12.4.1 Wholesale Price Contract
549(2)
12.4.2 Buyback Contract
551(2)
12.4.3 Revenue-Sharing Contract
553(1)
12.4.4 Service-Level Agreements
554(1)
12.4.5 Challenges Implementing Coordinating Agreements
554(1)
12.5 Summary
555(1)
Problems
555(1)
References
556(5)
Section V Production Management
13 An Overall Framework for Production Planning and Scheduling
561(20)
13.1 Characteristics of Different Production Processes
561(3)
13.2 A Framework for Production Decision Making
564(7)
13.2.1 A Review of Anthony's Hierarchy of Managerial Decisions
564(1)
13.2.2 Integration at the Operational Level
565(1)
13.2.3 The Framework
565(6)
13.3 Options in Dealing with the Hierarchy of Decisions
571(5)
13.3.1 Monolithic Modeling Approach
571(1)
13.3.2 Implicit Hierarchical Planning
572(1)
13.3.3 Explicit Hierarchical Planning
572(1)
13.3.4 The Hax—Meal Hierarchical Planning System
573(3)
13.4 Summary
576(1)
Problems
577(1)
References
577(4)
14 Medium-Range Aggregate Production Planning
581(40)
14.1 The Aggregate Planning Problem
581(4)
14.2 The Costs Involved
585(5)
14.2.1 Costs of Regular-Time Production
585(2)
14.2.2 Overtime Costs
587(1)
14.2.3 Costs of Changing the Production Rate
587(1)
14.2.4 Inventory Associated Costs
588(1)
14.2.5 Costs of Insufficient Capacity in the Short Run
589(1)
14.3 The Planning Horizon
590(1)
14.4 Two Pure Strategies: Level and Chase
591(1)
14.5 Feasible Solution Methods
592(7)
14.5.1 General Comments
592(1)
14.5.2 An Example of a Graphic—Tabular Method
593(6)
14.6 Linear Programming Models
599(4)
14.6.1 Strengths and Weaknesses
601(1)
14.6.2 The Inclusion of Integer Variables in LP Formulations
602(1)
14.6.3 The Land Algorithm
603(1)
14.7 Simulation Search Procedures
603(2)
14.8 Modeling the Behavior of Managers
605(2)
14.8.1 Management Coefficients Models
605(2)
14.8.2 Manpower Decision Framework
607(1)
14.9 Planning for Adjustments Recognizing Uncertainty
607(2)
14.9.1 The Production-Switching Heuristic
608(1)
14.10 Summary
609(1)
Problems
610(7)
References
617(4)
15 Material Requirements Planning and Its Extensions
621(40)
15.1 The Complexity of Multistage Assembly Manufacturing
622(1)
15.2 The Weaknesses of Traditional Replenishment Systems in a Manufacturing Setting
623(1)
15.3 Closed-Loop MRP
624(2)
15.4 Material Requirements Planning
626(16)
15.4.1 Some Important Terminology
626(4)
15.4.2 Information Required for MRP
630(1)
15.4.3 The General Approach of MRP
630(3)
15.4.4 A Numerical Illustration of the MRP Procedure
633(6)
15.4.5 The Material Requirements Plan and Its Uses
639(1)
15.4.6 Low-Value, Common-Usage Items
639(1)
15.4.7 Pegging
639(1)
15.4.8 Handling Requirements Updates
640(1)
15.4.9 Coping with Uncertainty in MRP
641(1)
15.5 Capacity Requirements Planning
642(2)
15.6 Distribution Requirements Planning
644(1)
15.7 Weaknesses of MRP
645(2)
15.8 ERP Systems
647(3)
15.8.1 Enhancements to ERP Systems
649(1)
15.9 Summary
650(1)
Problems
650(6)
References
656(5)
16 Just-in-Time, Optimized Production Technology and Short-Range Production Scheduling
661(52)
16.1 Production Planning and Scheduling in Repetitive Situations: Just-in-Time
662(9)
16.1.1 Philosophy of JIT
662(2)
16.1.2 Kanban Control System
664(5)
16.1.3 Benefits and Weaknesses of JIT
669(2)
16.2 Planning and Scheduling in Situations with Bottlenecks: Optimized Production Technology
671(8)
16.2.1 Philosophy of OPT
671(5)
16.2.2 Drum-Buffer-Rope Scheduling
676(1)
16.2.3 A Related System: CONWIP
677(1)
16.2.4 Benefits and Weaknesses of OPT
678(1)
16.3 Short-Range Production Scheduling
679(20)
16.3.1 Issues in Short-Term Scheduling
680(4)
16.3.2 Techniques for Short-Term Scheduling
684(4)
16.3.3 Deterministic Scheduling of a Single Machine: Priority Sequencing Rules
688(4)
16.3.4 General Job Shop Scheduling
692(7)
16.4 Summary
699(1)
Problems
699(4)
Appendix 16A: Proof that SPT Minimizes Total Flowtime
703(1)
References
704(9)
17 Summary
713(4)
17.1 Operations Strategy
713(1)
17.2 Changing the Givens
714(1)
17.3 Future Developments
715(2)
Appendix I: Elements of Lagrangian Optimization 717(6)
Appendix II: The Normal Probability Distribution 723(20)
Appendix III: Approximations and Excel Functions 743(6)
Author Index 749(18)
Subject Index 767
Edward A. Silver, David F. Pyke, Douglas J. Thomas
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