Production and Operations Analysis

Transcription

1 Production and Operations Analysis Sixth Edition Steven Nahmias Santa Clara University Me Graw Hill Boston Burr Ridge, IL Dubuque, IA Madison, Wl New York San Francisco St. Louis Bangkok Bogota Caracas Kuala Lumpur Lisbon London Madrid Mexico City Milan Montreal New Delhi Santiago Seoul Singapore Sydney Taipei Toronto

2 Contents About the Author xv Preface xvi Introduction xvii Chapter 1 Strategy and Competition 1 Chapter Overview 1 Snapshot Application: Apple Adopts a New Business Strategy and Shifts Its Core Competency from Computers to Portable Music Manufacturing Matters 5 Manufacturing Jobs Outlook A Framework for Operations Strategy 7 Strategic Dimensions The Classical View of Operations Strategy S Time Horizon 9 Focus 11 Evaluation 12 Consistency Competing in the Global Marketplace 14 Problems for Sections Snapshot Application: Global Manufacturing Strategies in the Automobile Industry Strategic Initiatives: Reengineering the Business Process Strategic Initiatives: Just-in-Time Strategic Initiatives: Time-Based Competition Strategic Initiatives: Competing on Quality 24 Problems for Sections Matching Process and Product Life Cycles 27 The Product Life Cycle 2 7 The Process Life Cycle 28 The Product-Process Matrix 29 Problems for Section Learning and Experience Curves 31 Learning Curves 32 Experience Curves 34 Learning and Experience Curves and Manufacturing Strategy 36 Problems for Section Capacity Growth Planning: A Long-Term Strategic Problem 38 Economies of Scale and Economies of Scope 38 Make or Buy: A Prototype Capacity Expansion Problem 39 Dynamic Capacity Expansion Policy 40 Issues in Plant Location 44 Problems for Section Summary 47 Additional Problems for Chapter 1 48 Appendix 1-A Present Worth Calculations Bibliography 51 Chapter 2 Forecasting 52 Chapter Overview The Time Horizon in Forecasting Characteristics of Forecasts Subjective Forecasting Methods Objective Forecasting Methods 57 Causal Models 57 Time Series Methods 58 Snapshot Application: Advanced Forecasting, Inc., Serves the Semiconductor Industry 59 Problems for Sections Notation Conventions Evaluating Forecasts 61 Problems for Section Methods for Forecasting Stationary Series 64 Moving Averages 64 Problems on Moving Averages 67 Exponential Smoothing 67 Multiple-Step-Ahead Forecasts 71 Comparison of Exponential Smoothing and Moving A verages 72 Problems for Section Snapshot Application: Sport Obermeyer Slashes Costs with Improved Forecasting Trend-Based Methods 75 Regression Analysis 75 Problems for Section Double Exponential Smoothing Using Holt's Method 77 More Problems for Section

3 viii Contents 2.9 Methods for Seasonal Series 79 Seasonal Factors for Stationary Series 79 Seasonal Decomposition Using Moving Averages 81 Problems for Section Winters s Method for Seasonal Problems 84 More Problems for Section Box-Jenkins Models 89 Estimating the Autocorrelation Function 90 The Autoregressive Process 93 The Moving-Average Process 94 Mixtures: ARMA Models 96 ARIMA Models 96 Using ARIMA Models for Forecasting 98 Summary of the Steps Required for Building ARIMA Models 99 Case Study: Using Box-Jenkins Methodology to Predict Monthly International Airline Passenger Totals 100 Snapshot Application: A Simple ARIMA Model Predicts the Performance of the U.S. Economy 104 Box-Jenkins Modeling A Critique 104 Problems for Section Practical Considerations 105 Model Identification and Monitoring 105 Simple versus Complex Time Series Methods Overview of Advanced Topics in Forecasting 107 Simulation as a Forecasting Tool 107 Forecasting Demand in the Presence of Lost Sales d.3 Linking Forecasting and Inventory Management 110 Snapshot Application: Predicting Economic Recessions Historical Notes and Additional Topics Summary 113 Additional Problems on Forecasting 113 Appendix 2-A Forecast Errors for Moving Averages and Exponential Smoothing 118 Appendix 2-B Derivation of the Equations for the Slope and Intercept for Regression Analysis 120 Appendix 2-C Glossary of Notation for Chapter Bibliography 122 Chapter 3 Aggregate Planning 124 Chapter Overview Aggregate Units of Production Overview of the Aggregate Planning Problem Costs in Aggregate Planning 130 Problems for Sections A Prototype Problem 133 Evaluation of a Chase Strategy (Zero Inventory Plan) 135 Evaluation of the Constant Workforce Plan 136 Mixed Strategies and Additional Constraints 138 Problems for Section Solution of Aggregate Planning Problems by Linear Programming 141 Cost Parameters and Given Information 141 Problem Variables 142 Problem Constraints 142 Rounding the Variables 143 Extensions 144 Other Solution Methods Solving Aggregate Planning Problems by Linear Programming: An Example 147 Problems for Sections 3.5 and The Linear Decision Rule Modeling Management Behavior 153 Problems for Sections 3.7 and Disaggregating Aggregate Plans 155 Snapshot Application: Welch's Uses Aggregate Plann ing for Production Scheduling 157 Problems for Section Production Planning on a Global Scale Practical Considerations Historical Notes Summary 161 Additional Problems on Aggregate Planning 162 Appendix 3-A Glossary of Notation for Chapter Bibliography 168 Supplement 1 Linear Programming Introduction A Prototype Linear Programming Problem Statement of the General Problem 171 Definitions of Commonly Used Terms 172 Features of Linear Programs 173

4 Contents ix ST.4 Solving Linear Programming Problems Graphically 174 Graphing Linear Inequalities 174 Graphing the Feasible Region 176 Finding the Optimal Solution 177 Identifying the Optimal Solution Directly by Graphical Means The Simplex Method: An Overview Solving Linear Programming Problems with Excel 181 Entering Large Problems Efficiently Interpreting the Sensitivity Report 187 Shadow Prices 187 Objective Function Coefficients and Right- Hand Sides 188 Adding a New Variable 188 Using Sensitivity Analysis Recognizing Special Problems 191 Unbounded Solutions 191 Empty Feasible Region 192 Degeneracy 194 Multiple Optimal Solutions 194 Redundant Constraints The Application of Linear Programming to Production and Operations Analysis 195 Bibliography 197 Chapter 4 Inventory Control Subject to Known Demand 198 Chapter Overview Types of Inventories Motivation for Holding Inventories Characteristics of Inventory Systems Relevant Costs 204 Holding Cost 204 Order Cost 206 Penalty Cost 207 Problems for Sections The EOQ Model 210 The Basic Model 210 Inclusion of Order Lead Time 213 Sensitivity 214 EOQ and JIT 215 Problems for Section Extension to a Finite Production Rate 218 Problems for Section Quantity Discount Models 220 Optimal Policy for All-Units Discount Schedule 221 Summary, of the Solution Technique for AlUUnits Discounts 223 Incremental Quantity Discounts 223 Summary, of the Solution Technique for Incremental Discounts 225 Other Discount Schedules 225 Problems for Section *4.8 Resource-Constrained Multiple Product Systems 227 Problems for Section EOQ Models for Production Planning 230 ProblemsfanSection Power-of-Two Policies Historical Notes and Additional Topics 237 Snapshot Application: Mervyn 's Recognized for State-of-the-Art Inventory Control System Summary 239 Additional Problems on Deterministic Inventory Models 240 Appendix 4-A Mathematical Derivations for Multiproduct Constrained EOQ Systems 244 Append ix 4-B Glossary of Notation for Chapter Bibliography 246 Chapter 5 Inventory Control Subject to Uncertain Demand 248 Chapter Overview 248 Overview of Models Treated in This Chapter The Nature of Randomness Optimization Criterion 255 Problems for Sections 5.1 and The Newsboy Model 257 Notation 257 Development of the Cost Function 258 Determining the Optimal Policy 259 Optimal Policy for Discrete Demand 261 Extension to Include Starting Inventory 261 Snapshot Application: Using Inventory Models to Manage the Seed-Corn Supply Chain at Syngenta 262 Extension to Multiple Planning Periods 263 Problems for Section Lot Size-Reorder Point Systems 266 Describing Demand 267 Decision Variables 267

5 x Contents Derivation of the Expected Cost Function 267 The Cost Function 269 Inventory Level versus Inventory Position Service Levels in (Q, R) Systems 272 Type 1 Service 272 Type 2 Service 273 Optimal (Q, R) Policies Subject to Type 2 Constraint 274 Imputed Shortage Cost 275 Scaling of Lead Time Demand 2 76 Estimating Sigma When Inventory Control and Forecasting A re Linked 2 76 *Lead Time Variability 277 Calculations in Excel 278 Negative Safety Stock 2 78 Problems for Sections 5.4 and Additional Discussion of Periodic-Review Systems 281 (s, S) Policies 281 *Service Levels in Periodic-Review Systems 281 Problems for Section Snapshot Application: Tropicana Uses Sophisticated Modeling for Inventory Management Multiproduct Systems 283 ABCAnalysis 283 Exchange Curves 285 Problems for Section *5.8 Overview of Advanced Topics 289 Multi-echelon Systems 289 Perishable Inventory Problems 290 Snapshot Application: Triad's Inventory Systems Meet Markets 'Needs Historical Notes and Additional Readings Summary 293 Additional Problems on Stochastic Inventory Models 294 Appendix 5-A Notational Conventions and Probability Review 300 Appendix 5-B Additional Results and Extensions for the Newsboy Model 301 Appendix 5-C Derivation of the Optimal (Q,R) Policy 304 Appendix 5-D Probability Distributions for Inventory Management 304 Appendix 5-E Glossary of Notation for Chapter Bibliography 309 Chapter 6 Supply Chain Management 311 Chapter Overview 311 The Supply Chain as a Strategic Weapon 315 Snapshot Application: Wal-Mart Wins with Solid Supply Chain Management The Transportation Problem 316 The Greedy Heuristic Solving Transportation Problems with Linear Programming Generalizations of the Transportation Problem 322 Infeasible Routes 323 Unbalanced Problems More General Network Formulations 324 Problems for Sections Snapshot Application: IBM Streamlines Its Supply Chain for Spare Parts Using Sophisticated Mathematical Models Distribution Resource Planning 330 Problems for Section Determining Delivery Routes in Supply Chains 332 Practical Issues in Vehicle Scheduling 336 Snapshot Application: Air Products Saves Big with Routing and Scheduling Optimizer 337 Problems for Section Designing Products for Supply Chain Efficiency 338 Postponement in Supply Chains 339 Additional Issues in Supply Chain Design 340 Snapshot Application: Dell Computer Designs the Ultimate Supply Chain 342 Problems for Section The Role of Information in the Supply Chain 343 The Bullwhip Effect 344- Snapshot Application: Saturn Emerges as an Industry Leader with Scientific Supply Chain Management 347 Electronic Commerce 347 Electronic Data Interchange 348 Web-Based Transactions Systems 349 RFID Technology Provides Faster Product Flow 350 Problems for Section Multilevel Distribution Systems 351 Problems for Section

6 Contents xi 6.10 Designing the Supply Chain in a Global Environment 355 Snapshot Application: Norwegian Company Implements Decision Support System to Streamline Its Supply Chain 356 Snapshot Application: Timken Battles Imports with Bundling 358 Supply Chain Management in a Global Environment 359 Snapshot Application: Digital Equipment Corporation Uses Mathematical Modeling to Plan Its Global Supply Chain 360 Trends in Offshore Outsourcing 360 Problems for Section Summary 362 Bibliography 362 Chapter 7 Push and Pull Production Control Systems: MRP and JIT 364 Chapter Overview 364 MRP Basics 367 JIT Basics The Explosion Calculus 370 Problems for Section Alternative Lot-Sizing Schemes 376 EOQ Lot Sizing 376 The Silver-Meal Heuristic 377 Least Unit Cost 378 Part Period Balancing 3 79 Problems for Section Incorporating Lot-Sizing Algorithms into the Explosion Calculus. 382 Problems for Section Lot Sizing with Capacity Constraints 384 Problems for Section Shortcomings of MRP 388 Uncertainty 388 Capacity Planning 389 Rolling Horizons and System Nervousness 390 Additional Considerations 392 Snapshot Application: Raymond Corporation Builds World-Class Manufacturing with MRP II 393 Problems for Section JIT Fundamentals 395 The Mechanics ofkanban 395 Single Minute Exchange of Dies 397 Advantages and Disadvantages of the Justin-Time Philosophy 398 Implementation of JIT in the United States 401 Problems for Section A Comparison of MRP and JIT JIT or Lean Production? Historical Notes Summary 406 Additional Problems for Chapter Appendix 7-A Optimal Lot Sizing for Time-Varying Demand 411 Appendix 7-B Glossary of Notation for Chapter Bibliography 416 Chapter 8 Operations Scheduling 417 Chapter Overview Production Scheduling and the Hierarchy of Production Decisions Important Characteristics of Job Shop Scheduling Problems 422 Objectives of Job Shop Management Job Shop Scheduling Terminology A Comparison of Specific Sequencing Rules 425 First-Come, First-Served 425 Shortest Processing Time 426 Earliest Due Date 426 Critical Ratio Scheduling Objectives in Job Shop Management: An Example 428 Problems for Sections An Introduction to Sequencing Theory for a Single Machine 430 Shortest-Processing-Time Scheduling 431 Earliest-Due-Date Scheduling 432 Minimizing the Number of Tardy Jobs 432 Precedence Constraints: Lawler's Algorithm 433 Snapshot Application: Millions Saved with Scheduling System for Fractional Aircraft Operators 435 Problems for Section Sequencing Algorithms for Multiple Machines 437 Scheduling n Jobs on Two Machines 438 Extension to Three Machines 439 The Two-Job Flow Shop Problem 441 Problems for Section Stochastic Scheduling: Static Analysis 445 Single Machine 445 Multiple Machines 446

7 xii Contents The Two-Machine Flow Shop Case- 447 Problems for Section Stochastic Scheduling: Dynamic Analysis 449 Selection Disciplines Independent of Job Processing Times 451 Selection Disciplines Dependent on Job Processing Times. 452 The cfi Rule 454 Problems for Section Assembly Line Balancing 455 Problems for Section Snapshot Application: Manufacturing Divisions Realize Savings with Scheduling Software Simulation: A Valuable Scheduling Tool Post-MRP Production Scheduling Software Historical Notes Summary 464 Additional Problems on Scheduling 465 Bibliography 471 Supplement 2 Queuing Theory Introduction Structural Aspects of Queuing Models Notation Little's Formula The Exponential and Poisson Distributions in Queuing 476 Aside 477' 52.6 Birth and Death Analysis for the M/M/l Queue Calculation of the Expected System Measures for the M/M/l Queue The Waiting Time Distribution Solution of the General Case Multiple Servers in Parallel: The M/M/c Queue The M/M/l Queue with a Finite Capacity Results for Nonexponential Service Distributions The M/G/oo. Queue Optimization of Queuing Systems 495 Typical Service System Design Problems 495 Modeling Framework Simulation of Queuing Systems 498 Bibliography 499 Chapter 9 Project Scheduling 500 Chapter Overview Representing a Project as a Network Critical Path Analysis 505 Finding the Critical Path 508 Problems for Sections 9.1 and Time Gosting Methods 513 Problems for Section Solving Critical Path Problems with Linear Programming 518 Linear Programming Formulation of the Cost-Time Problem 521 Problems for Section :5". PERT: Project Evaluation and Review Technique 523 Path Independence 528 Problems for Section Snapshot Application: Warner Robins Streamlines Aircraft Maintenance with CCPM Project Management Resource Considerations 533 Resource Constraints for Single-Project Scheduling 533 Resource Constraints for Multiproject Scheduling 535 Resource Loading Profiles 536 Problems for Section Organizational Issues in Project Management Historical Notes Project Management Software for the PC 542 Snapshot Application: Project Management Helps United Stay on Schedule 543 Snapshot Application: Thomas Brothers Plans Staffing with Project Management Software 543 Snapshot Application: Florida Power and Light Takes Project Management Seriously Summary 544 Additional Problems on Project Scheduling 545 Appendix 9-A Glossary of Notation for Chapter Bibliography 549

8 Contents xiii Chapter 10 Facilities Layout and Location 550 Chapter Overview 550 Snapshot Application: Sun Microsystems Pioneers New Flex Office System The Facilities Layout Problem Patterns of Flow 555 Activity Relationship Chart 555 From-To Chart Types of Layouts 559 Fixed Position Layouts 559 Product Layouts 559 Process Layouts 560 Layouts Based on Group Technology 560 Problems for Sections A Prototype Layout Problem and the Assignment Model 564 The Assignment Algorithm 565 Problems for Section *10.5 More Advanced Mathematical Programming Formulations 568 ProblemfarSection Computerized Layout Techniques 569 CRAFT 570 COFAD 574 ALDEP 575 CORELAP 576 PLANET 577 Computerized Methods versus Human Planners 577 Dynamic Plant Layouts 5 78 Other Computer Methods 578 Problems for Section Flexible Manufacturing Systems 582 Advantages of Flexible Manufacturing Systems 584 Disadvantages of Flexible Manufacturing Systems 584 Decision Making and Modeling of the FMS 585 The Future of FMS 588 Problems for Section Locating New Facilities 590 Snapshot Application: Kraft Foods Uses Optimization and Simulation to Determine Best Layout 591 Measures of Distance 592 Problems for Section The Single-Facility Rectilinear Distance Location Problem 593 Contour Lines 596 Minimax Problems 597 Problems for Section Euclidean Distance Problems 601 The Gravity Problem 601 The Straight-Line Distance Problem 602 Problems for Section Other Location Models 604 Locating Multiple Facilities 605 Further Extensions 606 Problems for Section Historical Notes Summary 610 Additional Problems on Layout and Location 611 Spreadsheet Problems for Chapter Appendix 10-A Finding Centroids 617 Appendix 10-B Computing Contour Lines 619 Bibliography 622 Chapter 11 Quality and Assurance 624 Chapter Overview 624 Overview of This Chapter Statistical Basis of Control Charts 629 Problems for Section Control Charts for Variables: The X and R Charts 633 X Charts 636 Relationship to Classical Statistics 636 R Charts 638 Problems for Section Control Charts for Attributes: The p Chart 641 p Charts for Varying Subgroup Sizes 643 Problems for Section Thee Chart 646 Problems for Section Classical Statistical Methods and Control Charts 649 Problem for Section *11.6 Economic Design of X Charts 650 Problems for Section

9 xiv Contents 11.7 Overview of Acceptance Sampling 657 Snapshot Application: Navistar Scores with Six-Sigma Quality Program Notation Single Sampling for Attributes 660 Derivation of the OC Curve 662 Problems for Section * Double Sampling Plans for Attributes 665 Problems for Section Sequential Sampling Plans 667 ProblemsfarSectionll.il Average Outgoing Quality 672 Snapshot Application: Motorola Leads the Way with Six-Sigma Quality Programs 674 Problems for Section Total Quality Management 675 Definitions 675 Listening to the Customer 675 Competition Based on Quality 677 Organizing for Quality 678 Benchmarking Quality 679 The Deming Prize and the Baldrige Award 680 ISO Quality: The Bottom Line Designing Quality into the Product 684 Design, Manufacturing, and Quality Historical Notes Summary 689 Additional Problems on Quality and Assurance 691 Appendix 11-A Approximating Distributions 695 Append ix 11 -B Glossary of Notation for Chapter 11 on Quality and Assurance 697 Bibliography 698 Chapter 12 Reliability and Maintainability 700 Chapter Overview Reliability of a Single Component 704 Introduction to Reliability Concepts 704 Preliminary Notation and Definitions 705 The Exponential Failure Law 707 Problems for Section Increasing and Decreasing Failure Rates 712 Problems for Section The Poisson Process in Reliability Modeling 715 Series Systems Subject to Purely Random Failures 718 Problems for Section Failures of Complex Equipment 720 Components in Series 720 Components in Parallel 721 Expected Value Calculations 721 K Out of N Systems 722 Problems for Section Introduction to Maintenance Models Deterministic Age Replacement Strategies 726 The Optimal Policy in the Basic Case 726 A General Age Replacement Model 728 Problems for Section Planned Replacement under Uncertainty 732 Planned Replacement for a Single Item 732 Block Replacement for a Group of Items 736 Problems for Section *12.8 Analysis of Warranty Policies 740 The Free Replacement Warranty 740 The Pro Rata Warranty 742 Extensions and Criticisms 744 Problems for Section Software Reliability 745 Snapshot Application: Reliability-Centered Maintenance Improves Operations at Three Mile Island Nuclear Plant Historical Notes Summary 748 Additional Problems on Reliability and Maintainability 749 Appendix 12-A Glossary of Notation on Reliability and Maintainability 751 Bibliography 753 Appendix: Tables 754 Index 772