Supply Chain Engineering Models and Applications

Supply Chain Engineering Models and Applications

A. Ravi Ravindran Donald P. Warsing, Jr.

CRC Press Taylor & Francis Group Boca Raton London New York CRC Press is an imprint of the Taylor & Francis Croup, an informa business

Contents Preface Acknowledgments Authors 1. Introduction to Supply Chain Engineering 1.1 Understanding Supply Chains 1.1.1 Flows in Supply Chains 1.2 Meaning of Supply Chain Engineering 1.3 Supply Chain Decisions 1.3.1 Strategic Decisions 1.3.2 Tactical Decisions 1.3.3 Operational Decisions 1.4 Enablers and Drivers of Supply Chain Performance 1.4.1 Supply Chain Enablers 1.4.2 Supply Chain Drivers 1.4.2.1 Inventory 1.4.2.2 Transportation 1.4.2.3 Facilities 1.4.2.4 Suppliers 1.5 Assessing and Managing Supply Chain Performance 1.5.1 Supply Chain Efficiency 1.5.2 Supply Chain Responsiveness 1.5.3 Supply Chain Risk 1.5.4 Conflicting Criteria in Supply Chain Optimization 1.6 Relationship between Supply Chain Metrics and Financial Metrics 1.6.1 Inventory Measures 1.6.1.1 Inventory Turns 1.6.1.2 Days of Inventory 1.6.1.3 Inventory Capital 1.6.2 Business Financial Measures 1.6.2.1 Return on Assets 1.6.2.2 Working Capital 1.6.2.3 Cash-to-Cash Cycle 1.7 Importance of Supply Chain Management 1.7.1 Supply Chain Top 25 1.8 Organization of the Textbook 1.8.1 Chapter 2 (Planning Production in Supply Chains) 1.8.2 Chapter 3 (Inventory Management Methods and Models)

xvii xxi xxiii 1 2 4 4 5 5 6 6 7 7 8 8 8 9 9 9 10 12 12 13 13 13 13 14 14 15 15 15 15 16 17 18 19 19 vii

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Contents

1.8.3

Chapter 4 (Transportation Decisions in Supply Chain Management) 1.8.4 Chapter 5 (Location and Distribution Decisions in Supply Chains) 1.8.5 Chapter 6 (Supplier Selection Models and Methods) 1.8.6 Chapter 7 (Managing Risks in Supply Chains) 1.8.7 Chapter 8 (Global Supply Chain Management) 1.9 Summary and Further Readings 1.9.1 Summary 1.9.2 Further Readings Exercises References

20 20 21 21 21 22 22 22 23 25

2. Planning Production in Supply Chains 27 2.1 Role of Demand Forecasting in Supply Chain Management 27 2.2 Forecasting Process 28 2.3 Qualitative Forecasting Methods 29 2.3.1 Executive Committee Consensus 29 2.3.2 Delphi Method 30 2.3.3 Survey of Sales Force 30 2.3.4 Customer Surveys 31 2.4 Quantitative Forecasting Methods 31 2.4.1 Time Series Forecasting 31 2.4.2 Constant Level Forecasting Methods 33 2.4.3 Last Value Method 34 2.4.4 Averaging Method 34 2.4.5 Simple Moving Average Method 35 2.4.6 Weighted Moving Average Method 35 2.4.7 Computing Optimal Weights by Linear Programming Model 36 2.4.8 Exponential Smoothing Method 38 2.5 Incorporating Seasonality in Forecasting 39 2.6 Incorporating Trend in Forecasting 42 2.6.1 Simple Linear Trend Model 43 2.6.2 Holt's Method 45 2.7 Incorporating Seasonality and Trend in Forecasting 47 2.7.1 Method Using Static Seasonality Indices 47 2.7.2 Winters' Method 49 2.8 Forecasting for Multiple Periods 51 2.8.1 Multi-Period Forecasting under Constant Level 51 2.8.2 Multi-Period Forecasting with Seasonality 52 2.8.3 Multi-Period Forecasting with Trend 52 2.8.4 Multi-Period Forecasting with Seasonality and Trend....53 2.9 Forecasting Errors 54 2.10 Monitoring Forecast Accuracy 57

Contents

2.11 Forecasting Software 2.11.1 Types of Forecasting Software 2.11.2 User Experience with Forecasting Software 2.12 Forecasting in Practice 2.12.1 Real World Applications 2.12.2 Forecasting in Practice: Survey Results 2.13 Production Planning Process 2.14 Aggregate Planning Problem 2.15 Linear Programming Model for Aggregate Planning 2.16 Nonlinear Programming Model for Aggregate Planning 2.17 Aggregate Planning as a Transportation Problem 2.17.1 Basic Transportation Problem 2.17.2 Aggregate Planning as a Transportation Problem 2.17.3 Greedy Algorithm for Aggregate Planning 2.18 Aggregate Planning Strategies: A Comparison 2.19 Summary and Further Readings 2.19.1 Demand Forecasting: Summary 2.19.2 ARIMA Method 2.19.3 Croston's Method 2.19.4 Further Readings in Forecasting 2.19.5 Production Planning: Further Readings 2.19.6 Managing Demand 2.19.7 Bullwhip Effect 2.19.8 Collaborative Planning, Forecasting and Replenishment (CPFR) Exercises References 3. Inventory Management Methods and Models 3.1 Decision Framework for Inventory Management 3.2 Some Preliminary Modeling Issues 3.2.1 Two Critical Tasks 3.2.2 ABC Analysis 3.3 Single-Item, Single-Period Problem: The Newsvendor 3.3.1 Service Measures in Inventory Models 3.3.2 Service Impact of Shortage Costs 3.3.3 Safety Stock: A First Look 3.4 Single-Item, Multi-Period Problems 3.4.1 Continuous-Review: Reorder Point-Order Quantity Model 3.4.2 Continuous-Review under Uncertainty 3.4.3 Periodic-Review, Reorder-Point-Order-up-to Models 3.4.4 Other Periodic-Review Inventory Models 3.4.5 Non-Stationary Demand: Distribution Requirements Planning

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59 59 61 61 61 62 63 64 65 70 72 72 75 78 80 81 81 81 82 82 83 83 84 85 85 92 95 95 98 98 99 101 105 106 108 108 110 115 121 125 127

Contents

3.5 3.6

Multi-Item Inventory Models Multi-Echelon Inventory Systems 3.6.1 Centralized versus Decentralized Control 3.6.2 Serial Supply Chain with Deterministic Demand and Fixed Ordering Costs 3.6.3 Two-Stage Serial System under Decentralized Control 3.6.4 Two-Stage Serial System under Centralized Control 3.6.5 Serial Supply Chain with Stochastic Demand and Negligible Fixed Ordering Costs 3.6.6 Serial Supply Chain with Fixed Costs and Stochastic Demand 3.7 Summary and Further Readings 3.7.1 Summary 3.7.2 Further Readings 3.A Appendix: The Bullwhip Effect Appendix References Exercises References

133 136 139 140 141 143 146 151 152 152 153 154 165 166 171

4. Transportation Decisions in Supply Chain Management 4.1 Introduction 4.2 Motor Carrier Freight: Truckload Mode 4.2.1 Accounting for Goods in Transit 4.3 Stepping Back: Freight Transportation Overview 4.4 More General Models of Freight Rates 4.5 Building A Rate Model: LTL Service 4.5.1 LTL Mode: Building the Inventory Decision Model 4.5.2 LTL Mode: Discount from Published Tariff 4.6 A More General Rate Model for LTL Service 4.7 Beyond Truck Transport: Rail and Air Cargo 4.8 Summary and Further Readings 4.8.1 Summary 4.8.2 Further Readings Exercises References

175 175 176 180 184 187 190 194 199 211 214 219 219 219 220 225

5. Location and Distribution Decisions in Supply Chains 5.1 Modeling with Binary Variables 5.1.1 Capital Budgeting Problem 5.1.2 Fixed Charge Problem 5.1.3 Constraint with Multiple Right-Hand-Side Constants 5.1.4 Quantity Discounts

229 230 230 231 232 233

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5.1.5 5.1.6

Handling Nonlinear Integer Programs Set Covering and Set Partitioning Models 5.1.6.1 Set Covering Problem 5.1.6.2 Set Partitioning Problem 5.1.6.3 Application to Warehouse Location 5.2 Supply Chain Network Optimization 5.2.1 Warehouse Location 5.2.2 Distribution Planning 5.2.3 Location-Distribution Problem 5.2.4 Location-Distribution with Dedicated Warehouses 5.2.5 Supply Chain Network Design 5.3 Risk Pooling or Inventory Consolidation 5.3.1 Principles of Risk Pooling 5.3.2 General Risk Pooling Model 5.3.3 Pros and Cons of Risk Pooling 5.3.4 Risk Pooling under Demand Uncertainty 5.3.5 Risk Pooling Example 5.3.6 Practical Uses of Risk Pooling 5.4 Continuous Location Models 5.4.1 Continuous Location Model: Single Facility 5.4.1.1 Gravity Model 5.4.1.2 Iterative Method 5.4.1.3 Illustrative Example: Gravity Model 5.4.1.4 Limitations of Gravity Model 5.4.2 Multiple Facility Location 5.5 Real-World Applications 5.5.1 Multi-National Consumer Products Company 5.5.1.1 Case 1: Supply Chain Network Design 5.5.1.2 Case 2: Distribution Planning 5.5.2 Procter and Gamble (P&G) 5.5.3 Ford Motor Company 5.5.4 Hewlett-Packard (HP) 5.5.5 BMW 5.5.6 AT&T 5.5.7 United Parcel Service (UPS) 5.6 Summary and Further Readings 5.6.1 Summary 5.6.2 Further Readings 5.6.2.1 Multiple Criteria Models for Network Design 5.6.2.2 Risk Pooling 5.6.2.3 Facility Location Decisions 5.6.2.4 Case Studies Exercises References

236 238 238 240 240 241 241 242 244 247 249 253 253 256 259 260 263 265 266 266 266 267 268 271 271 272 272 273 274 274 275 276 276 277 277 279 279 279 279 280 281 282 282 291

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Contents

6. Supplier Selection Models and Methods 293 6.1 Supplier Selection Problem 293 6.1.1 Introduction 293 6.1.2 Supplier Selection Process 294 6.1.3 In-House or Outsource 295 6.1.4 Chapter Overview 296 6.2 Supplier Selection Methods 296 6.2.1 Sourcing Strategy 296 6.2.2 Criteria for Selection 297 6.2.3 Pre-Qualification of Suppliers 299 6.2.4 Final Selection 300 6.2.4.1 Single Sourcing Methods 300 6.2.4.2 Multiple Sourcing Methods 303 6.3 Multi-Criteria Ranking Methods for Supplier Selection 308 6.3.1 Ranking of Suppliers 309 6.3.1.1 Case Study 1: Ranking of Suppliers 309 6.3.2 Use of Lp Metric for Ranking Suppliers 311 6.3.2.1 Steps of the L2 Metric Method 312 6.3.3 Rating (Scoring) Method 312 6.3.4 Borda Count 314 6.3.5 Pair-Wise Comparison of Criteria 316 6.3.6 Scaling Criteria Values 317 6.3.6.1 Simple Scaling 317 6.3.6.2 Ideal Value Method 317 6.3.6.3 Simple Linearization (Linear Normalization) ....318 6.3.6.4 Use of Lp Norm (Vector Scaling) 318 6.3.6.5 Illustrative Example of Scaling Criteria Values.... 318 6.3.6.6 Simple Scaling Illustration 319 6.3.6.7 Scaling by Ideal Value Illustration 320 6.3.6.8 Simple Linearization (Linear Normalization) Illustration 320 6.3.6.9 Scaling by Lp Norm Illustration 321 6.3.7 Analytic Hierarchy Process 322 6.3.7.1 Basic Principles of AHP 322 6.3.7.2 Steps of the AHP Model 323 6.3.8 Cluster Analysis 326 6.3.8.1 Procedure for Cluster Analysis 328 6.3.9 Group Decision Making 329 6.3.10 Comparison of Ranking Methods 330 6.4 Multi-Objective Supplier Allocation Model 330 6.4.1 Notations Used in the Model 331 6.4.2 Mathematical Formulation of the Order Allocation Problem 332 6.4.3 Goal Programming Methodology 334 6.4.3.1 General Goal Programming Model 335

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6.4.4 6.4.5 6.4.6 6.4.7 6.4.8

Preemptive Goal Programming Non-Preemptive Goal Programming Tchebycheff (Min-Max) Goal Programming Fuzzy Goal Programming Case Study 2: Supplier Order Allocation 6.4.8.1 Preemptive Goal Programming Solution 6.4.8.2 Non-Preemptive Goal Programming 6.4.8.3 Tchebycheff Goal Programming 6.4.8.4 Fuzzy Goal Programming 6.4.9 Value Path Approach 6.4.9.1 Value Path Approach for the Supplier Selection Case Study 6.4.9.2 Discussion of Value Path Results 6.5 Summary and Further Readings 6.5.1 Ranking Suppliers 6.5.2 Supplier Order Allocation 6.5.3 Global Sourcing 6.5.4 Supplier Risk Exercises References 7. Managing Risks in Supply Chain 7.1 Supply Chain Risk 7.2 Real World Risk Events and Their Impacts 7.2.1 Importance of Supply Chain Risk Management 7.3 Sources of Supply Chain Risks 7.4 Risk Identification 7.5 ' Risk Assessment < 7.5.1 Risk Mapping 7.5.2 Risk Prioritization 7.5.2.1 Risk Priority Numbers 7.6 Risk Management 7.6.1 Risk Management Strategies 7.6.2 Developing a Risk Management Plan 7.6.3 Risk Mitigation Strategies 7.6.3.1 Traditional Strategies 7.6.3.2 Flexible Strategies 7.7 Best Industry Practices in Risk Management 7.7.1 Teradynelnc 7.7.2 Hewlett-Packard (HP) 7.7.3 Federal Express 7.7.4 Wal-Mart 7.7.5 Johnson and Johnson 7.8 Risk Quantification Models 7.8.1 Basic Risk Quantification Models

336 337 338 339 339 342 342 343 343 343 344 345 346 346 347 349 351 351 357 363 363 364 365 367 368 369 370 371 371 372 373 374 375 375 375 376 377 378 378 379 380 380 381

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7.9

7.10

7.11 7.12

7.13

Value-at-Risk (VaR) Models 7.9.1 VaR Type Impact Function 7.9.2 Generalized Extreme Value Distribution (GEVD) Functions for Risk Impact 7.9.3 Estimating GEVD Parameters 7.9.4 VaR Occurrence Functions 7.9.5 VaR Disruption Risk Function 7.9.5.1 Simulation Approach 7.9.5.2 VaR Type Occurrence Function 7.9.5.3 VaR Type Disruption Risk Function Miss-the-Target (MtT) Risk Models 7.10.1 MtT Type Impact Function 7.10.2 MtT Type Occurrence Function 7.10.2.1 Gamma Distribution for S-Type 7.10.2.2 Beta Distribution for the L-Type 7.10.2.3 Generalized Hyperbolic Distribution forN-Type 7.10.3 MtT Type Risk function 7.10.3.1 S-Type Risk Function 7.10.3.2 L-Type Risk 7.10.3.3 N-Type Risk Function Risk Measures Combining VaR and MtT Type Risks 7.12.1 Combining Different VaR Type or MtT Type Risks from the Same Supplier 7.12.1.1 VaR Type Risk Combination 7.12.1.2 MtT Type Risk Combination 7.12.2 Combining the Same VaR Type or MtT Type Risks from Different Suppliers 7.12.2.1 VaR Type Combination 7.12.2.2 MtT Type Risk Combination 7.12.3 Combining Total VaR Type or MtT Type Risks from All Suppliers 7.12.3.1 VaR Type Combination 7.12.3.2 MtT Type Combination Risk Detectability and Risk Recovery 7.13.1 Detectability of Disruptive Events 7.13.1.1 Some Basic Properties of Markov Chains 7.13.1.2 Computing the MFPT Matrix 7.13.1.3 Using MFPT in Disruption Risk Quantification 7.13.2 A Conceptual Model for Risk Recovery 7.13.3 Illustrative Example of Risk Detectability and Recovery

382 382 384 384 386 387 387 390 390 393 393 395 395 396 396 397 397 398 398 402 405 405 405 406 407 407 407 408 408 408 409 409 410 410 411 412 413

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7.14 Multiple Criteria Optimization Models for Supplier Selection Incorporating Risk 416 7.14.1 Phase 1 Model (Short-Listing Suppliers) 417 7.14.2 Results of Phase 1 Experiments 418 7.14.2.1 Ranking of the Criteria 418 7.14.2.2 Comparison across Methods for the Same DM 419 7.14.2.3 Comparison across DMs for the Same Method.... 419 7.14.2.4 Individual Supplier Rankings 420 7.14.2.5 Group Supplier Rankings 422 7.14.2.6 Conclusions from Phase I Results 423 7.14.3 Risk Adjusted Multi-Criteria Optimization Model for Supplier Sourcing (Phase 2) 423 7.14.3.1 Model Objectives 424 7.14.3.2 Model Constraints 425 7.14.4 Solution Methodology 426 7.14.4.1 Preemptive GP Model 426 7.14.4.2 Non-Preemptive GP Model 427 7.14.4.3 Tchebycheff (Min-Max) GP Model 428 7.14.4.4 Fuzzy GP Model 429 7.14.5 Data Description 429 7.14.5.1 MtT Type Risk Calculations 430 7.14.5.2 VaR Type Risk Calculations 431 7.14.6 Phase 2 Model Results 432 7.14.6.1 Preemptive GP Solution 432 7.14.6.2 Non-Preemptive GP Solution 433 7.14.6.3 Tchebycheff GP Solution 433 7.14.6.4 Fuzzy GP Solution 434 7.14.7 Comparison of Phase 2 Results 434 7.14.8 Discussion of the Results 436 7.15 Summary and Further Readings 436 7.15.1 Summary 436 7.15.1.1 Extensions 437 7.15.2 Literature on Supply Chain Risk Quantification and Management 438 7.15.2.1 Mathematical Models for Supply Chain Risk Quantification and Management 438 7.15.2.2 Conceptual Models for Supply Chain Risk Management 439 7.15.2.3 Surveys and Case Studies on Supply Chain Risk Management 439 Exercises 443 References 445

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8. Global Supply Chain Management 8.1 History of Globalization 8.2 Impacts of Globalization 8.2.1 Changes to World Economies 8.2.2 Global Products 8.2.3 Impact of Globalization in U.S. Manufacturing 8.2.4 Risks in Globalization 8.3 Managing Global Supply Chains 8.3.1 Global Risk Factors 8.3.2 Global Supply Chain Strategies 8.3.3 Examples of Globalization Strategies 8.4 Global Sourcing 8.4.1 Benefits and Barriers to Global Sourcing 8.4.1.1 Reasons for Global Sourcing 8.4.1.2 Barriers to Global Sourcing 8.4.2 Issues in Global Sourcing 8.4.2.1 Hidden Costs in Global Sourcing 8.4.3 Factors Affecting International Supplier Selection 8.4.3.1 Financial Issues 8.4.3.2 Logistics Issues 8.4.3.3 Manufacturing Practices 8.4.3.4 Strategic Issues 8.4.4 Tools for Global Sourcing 8.5 International Logistics 8.5.1 Steady Demand 8.5.2 High Demand Variability 8.6 Designing a Resilient Global Supply Chain: A Case Study 8.6.1 Problem Background 8.6.2 Model Features 8.6.3 Decision Criteria and Risk Assessment 8.6.4 Model Results and Managerial Insights 8.6.4.1 Results of Profit Maximization Model 8.6.4.2 Multi-Criteria Analysis 8.7 Summary and Further Readings 8.7.1 Summary 8.7.2 Further Readings Exercises References

449 449 450 450 451 453 454 455 455 456 457 458 459 459 459 460 460 461 461 463 463 464 465 466 467 467 467 468 470 470 474 474 475 477 477 478 479 485

Appendix A: Multiple Criteria Decision Making: An Overview

489

Index

509