Supply Chain Engineering Models and Applications

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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

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1.1 Understanding Supply Chains 2 1.1.1 Flows in Supply Chains 4 1.2 Meaning of Supply Chain Engineering 4 1.3 Supply Chain Decisions 5 1.3.1 Strategic Decisions 5 1.3.2 Tactical Decisions 6 1.3.3 Operational Decisions 6 1.4 Enablers and Drivers of Supply Chain Performance 7 1.4.1 Supply Chain Enablers 7 1.4.2 Supply Chain Drivers 8 1.4.2.1 Inventory 8 1.4.2.2 Transportation 8 1.4.2.3 Facilities 9 1.4.2.4 Suppliers 9 1.5 Assessing and Managing Supply Chain Performance 9 1.5.1 Supply Chain Efficiency 10 1.5.2 Supply Chain Responsiveness 12 1.5.3 Supply Chain Risk 12 1.5.4 Conflicting Criteria in Supply Chain Optimization 13 1.6 Relationship between Supply Chain Metrics and Financial

Metrics 13 1.6.1 Inventory Measures 13 1.6.1.1 Inventory Turns 13 1.6.1.2 Days of Inventory 14 1.6.1.3 Inventory Capital 14 1.6.2 Business Financial Measures 15 1.6.2.1 Return on Assets 15 1.6.2.2 Working Capital 15 1.6.2.3 Cash-to-Cash Cycle 15 1.7 Importance of Supply Chain Management 16 1.7.1 Supply Chain Top 25 17 1.8 Organization of the Textbook 18 1.8.1 Chapter 2 (Planning Production in Supply Chains) 19 1.8.2 Chapter 3 (Inventory Management Methods

and Models) 19

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viii Contents

1.8.3 Chapter 4 (Transportation Decisions in Supply

Chain Management) 20 1.8.4 Chapter 5 (Location and Distribution Decisions

in Supply Chains) 20 1.8.5 Chapter 6 (Supplier Selection Models and Methods) 21 1.8.6 Chapter 7 (Managing Risks in Supply Chains) 21 1.8.7 Chapter 8 (Global Supply Chain Management) 21 1.9 Summary and Further Readings 22 1.9.1 Summary 22 1.9.2 Further Readings 22 Exercises 23 References 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

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2.11 Forecasting Software 59 2.11.1 Types of Forecasting Software 59 2.11.2 User Experience with Forecasting Software 61 2.12 Forecasting in Practice 61 2.12.1 Real World Applications 61 2.12.2 Forecasting in Practice: Survey Results 62 2.13 Production Planning Process 63 2.14 Aggregate Planning Problem 64 2.15 Linear Programming Model for Aggregate Planning 65 2.16 Nonlinear Programming Model for Aggregate Planning 70 2.17 Aggregate Planning as a Transportation Problem 72 2.17.1 Basic Transportation Problem 72 2.17.2 Aggregate Planning as a Transportation Problem 75 2.17.3 Greedy Algorithm for Aggregate Planning 78 2.18 Aggregate Planning Strategies: A Comparison 80 2.19 Summary and Further Readings 81 2.19.1 Demand Forecasting: Summary 81 2.19.2 ARIMA Method 81 2.19.3 Croston's Method 82 2.19.4 Further Readings in Forecasting 82 2.19.5 Production Planning: Further Readings 83 2.19.6 Managing Demand 83 2.19.7 Bullwhip Effect 84 2.19.8 Collaborative Planning, Forecasting

and Replenishment (CPFR) 85 Exercises 85 References 92

3. Inventory Management Methods and Models 95

3.1 Decision Framework for Inventory Management 95 3.2 Some Preliminary Modeling Issues 98 3.2.1 Two Critical Tasks 98 3.2.2 ABC Analysis 99 3.3 Single-Item, Single-Period Problem: The Newsvendor 101 3.3.1 Service Measures in Inventory Models 105 3.3.2 Service Impact of Shortage Costs 106 3.3.3 Safety Stock: A First Look 108 3.4 Single-Item, Multi-Period Problems 108

3.4.1 Continuous-Review: Reorder Point-Order Quantity Model 110 3.4.2 Continuous-Review under Uncertainty 115 3.4.3 Periodic-Review, Reorder-Point-Order-up-to Models 121 3.4.4 Other Periodic-Review Inventory Models 125 3.4.5 Non-Stationary Demand: Distribution Requirements

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Contents

3.5 Multi-Item Inventory Models 133 3.6 Multi-Echelon Inventory Systems 136 3.6.1 Centralized versus Decentralized Control 139 3.6.2 Serial Supply Chain with Deterministic Demand

and Fixed Ordering Costs 140 3.6.3 Two-Stage Serial System under Decentralized

Control 141 3.6.4 Two-Stage Serial System under Centralized Control 143 3.6.5 Serial Supply Chain with Stochastic Demand and

Negligible Fixed Ordering Costs 146 3.6.6 Serial Supply Chain with Fixed Costs and Stochastic

Demand 151 3.7 Summary and Further Readings 152 3.7.1 Summary 152 3.7.2 Further Readings 153 3.A Appendix: The Bullwhip Effect 154 Appendix References 165 Exercises 166 References 171

4. Transportation Decisions in Supply Chain Management 175

4.1 Introduction 175 4.2 Motor Carrier Freight: Truckload Mode 176 4.2.1 Accounting for Goods in Transit 180 4.3 Stepping Back: Freight Transportation Overview 184 4.4 More General Models of Freight Rates 187 4.5 Building A Rate Model: LTL Service 190 4.5.1 LTL Mode: Building the Inventory Decision Model 194 4.5.2 LTL Mode: Discount from Published Tariff 199 4.6 A More General Rate Model for LTL Service 211 4.7 Beyond Truck Transport: Rail and Air Cargo 214 4.8 Summary and Further Readings 219 4.8.1 Summary 219 4.8.2 Further Readings 219 Exercises 220 References 225

5. Location and Distribution Decisions in Supply Chains 229

5.1 Modeling with Binary Variables 230 5.1.1 Capital Budgeting Problem 230 5.1.2 Fixed Charge Problem 231 5.1.3 Constraint with Multiple Right-Hand-Side

Constants 232 5.1.4 Quantity Discounts 233

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5.1.5 Handling Nonlinear Integer Programs 236 5.1.6 Set Covering and Set Partitioning Models 238 5.1.6.1 Set Covering Problem 238 5.1.6.2 Set Partitioning Problem 240 5.1.6.3 Application to Warehouse Location 240 5.2 Supply Chain Network Optimization 241 5.2.1 Warehouse Location 241 5.2.2 Distribution Planning 242 5.2.3 Location-Distribution Problem 244 5.2.4 Location-Distribution with Dedicated Warehouses 247 5.2.5 Supply Chain Network Design 249 5.3 Risk Pooling or Inventory Consolidation 253 5.3.1 Principles of Risk Pooling 253 5.3.2 General Risk Pooling Model 256 5.3.3 Pros and Cons of Risk Pooling 259 5.3.4 Risk Pooling under Demand Uncertainty 260 5.3.5 Risk Pooling Example 263 5.3.6 Practical Uses of Risk Pooling 265 5.4 Continuous Location Models 266 5.4.1 Continuous Location Model: Single Facility 266 5.4.1.1 Gravity Model 266 5.4.1.2 Iterative Method 267 5.4.1.3 Illustrative Example: Gravity Model 268 5.4.1.4 Limitations of Gravity Model 271 5.4.2 Multiple Facility Location 271 5.5 Real-World Applications 272 5.5.1 Multi-National Consumer Products Company 272 5.5.1.1 Case 1: Supply Chain Network Design 273 5.5.1.2 Case 2: Distribution Planning 274 5.5.2 Procter and Gamble (P&G) 274 5.5.3 Ford Motor Company 275 5.5.4 Hewlett-Packard (HP) 276 5.5.5 BMW 276 5.5.6 AT&T 277 5.5.7 United Parcel Service (UPS) 277 5.6 Summary and Further Readings 279 5.6.1 Summary 279 5.6.2 Further Readings 279

5.6.2.1 Multiple Criteria Models for Network

Design 279 5.6.2.2 Risk Pooling 280 5.6.2.3 Facility Location Decisions 281 5.6.2.4 Case Studies 282 Exercises 282 References 291

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xii 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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Contents xiii

6.4.4 Preemptive Goal Programming 336 6.4.5 Non-Preemptive Goal Programming 337 6.4.6 Tchebycheff (Min-Max) Goal Programming 338 6.4.7 Fuzzy Goal Programming 339 6.4.8 Case Study 2: Supplier Order Allocation 339 6.4.8.1 Preemptive Goal Programming Solution 342 6.4.8.2 Non-Preemptive Goal Programming 342 6.4.8.3 Tchebycheff Goal Programming 343 6.4.8.4 Fuzzy Goal Programming 343 6.4.9 Value Path Approach 343

6.4.9.1 Value Path Approach for the Supplier

Selection Case Study 344 6.4.9.2 Discussion of Value Path Results 345 6.5 Summary and Further Readings 346 6.5.1 Ranking Suppliers 346 6.5.2 Supplier Order Allocation 347 6.5.3 Global Sourcing 349 6.5.4 Supplier Risk 351 Exercises 351 References 357

7. Managing Risks in Supply Chain 363

7.1 Supply Chain Risk 363 7.2 Real World Risk Events and Their Impacts 364 7.2.1 Importance of Supply Chain Risk Management 365 7.3 Sources of Supply Chain Risks 367 7.4 Risk Identification 368 7.5 ' Risk Assessment < 369 7.5.1 Risk Mapping 370 7.5.2 Risk Prioritization 371 7.5.2.1 Risk Priority Numbers 371 7.6 Risk Management 372 7.6.1 Risk Management Strategies 373 7.6.2 Developing a Risk Management Plan 374 7.6.3 Risk Mitigation Strategies 375 7.6.3.1 Traditional Strategies 375 7.6.3.2 Flexible Strategies 375

7.7 Best Industry Practices in Risk Management 376

7.7.1 Teradynelnc 377 7.7.2 Hewlett-Packard (HP) 378 7.7.3 Federal Express 378 7.7.4 Wal-Mart 379 7.7.5 Johnson and Johnson 380 7.8 Risk Quantification Models 380 7.8.1 Basic Risk Quantification Models 381

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xiv Contents 7.9 Value-at-Risk (VaR) Models 382 7.9.1 VaR Type Impact Function 382 7.9.2 Generalized Extreme Value Distribution (GEVD)

Functions for Risk Impact 384 7.9.3 Estimating GEVD Parameters 384 7.9.4 VaR Occurrence Functions 386 7.9.5 VaR Disruption Risk Function 387 7.9.5.1 Simulation Approach 387 7.9.5.2 VaR Type Occurrence Function 390 7.9.5.3 VaR Type Disruption Risk Function 390 7.10 Miss-the-Target (MtT) Risk Models 393 7.10.1 MtT Type Impact Function 393 7.10.2 MtT Type Occurrence Function 395 7.10.2.1 Gamma Distribution for S-Type 395 7.10.2.2 Beta Distribution for the L-Type 396 7.10.2.3 Generalized Hyperbolic Distribution

forN-Type 396 7.10.3 MtT Type Risk function 397 7.10.3.1 S-Type Risk Function 397 7.10.3.2 L-Type Risk 398 7.10.3.3 N-Type Risk Function 398 7.11 Risk Measures 402 7.12 Combining VaR and MtT Type Risks 405

7.12.1 Combining Different VaR Type or MtT Type Risks

from the Same Supplier 405 7.12.1.1 VaR Type Risk Combination 405 7.12.1.2 MtT Type Risk Combination 406 7.12.2 Combining the Same VaR Type or MtT Type Risks

from Different Suppliers 407 7.12.2.1 VaR Type Combination 407 7.12.2.2 MtT Type Risk Combination 407 7.12.3 Combining Total VaR Type or MtT Type Risks

from All Suppliers 408 7.12.3.1 VaR Type Combination 408 7.12.3.2 MtT Type Combination 408 7.13 Risk Detectability and Risk Recovery 409 7.13.1 Detectability of Disruptive Events 409 7.13.1.1 Some Basic Properties of Markov Chains 410 7.13.1.2 Computing the MFPT Matrix 410 7.13.1.3 Using MFPT in Disruption Risk

Quantification 411 7.13.2 A Conceptual Model for Risk Recovery 412 7.13.3 Illustrative Example of Risk Detectability

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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 449

8.1 History of Globalization 449 8.2 Impacts of Globalization 450 8.2.1 Changes to World Economies 450 8.2.2 Global Products 451 8.2.3 Impact of Globalization in U.S. Manufacturing 453 8.2.4 Risks in Globalization 454 8.3 Managing Global Supply Chains 455 8.3.1 Global Risk Factors 455 8.3.2 Global Supply Chain Strategies 456 8.3.3 Examples of Globalization Strategies 457 8.4 Global Sourcing 458 8.4.1 Benefits and Barriers to Global Sourcing 459 8.4.1.1 Reasons for Global Sourcing 459 8.4.1.2 Barriers to Global Sourcing 459 8.4.2 Issues in Global Sourcing 460 8.4.2.1 Hidden Costs in Global Sourcing 460 8.4.3 Factors Affecting International Supplier Selection 461 8.4.3.1 Financial Issues 461 8.4.3.2 Logistics Issues 463 8.4.3.3 Manufacturing Practices 463 8.4.3.4 Strategic Issues 464 8.4.4 Tools for Global Sourcing 465 8.5 International Logistics 466 8.5.1 Steady Demand 467 8.5.2 High Demand Variability 467 8.6 Designing a Resilient Global Supply Chain: A Case Study 467 8.6.1 Problem Background 468 8.6.2 Model Features 470 8.6.3 Decision Criteria and Risk Assessment 470 8.6.4 Model Results and Managerial Insights 474 8.6.4.1 Results of Profit Maximization Model 474 8.6.4.2 Multi-Criteria Analysis 475 8.7 Summary and Further Readings 477 8.7.1 Summary 477 8.7.2 Further Readings 478 Exercises 479 References 485

Appendix A: Multiple Criteria Decision Making: An Overview 489