book

Supply Chain Engineering, 2nd Edition

Name: Supply Chain Engineering, 2nd Edition
ISBN: 9781000924015

by A. Ravi Ravindran, Donald P. Warsing, Jr., Paul M. Griffin

August 2023

Intermediate to advanced

642 pages

19h 30m

English

CRC Press

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Cover
Half Title
Series Page
Title Page
Copyright Page
Dedication
Table of Contents
Preface
Acknowledgments
Authors

Chapter 1 Introduction to Supply Chain Engineering
1.1 Understanding Supply Chains1.1.1 Flows in Supply Chains1.2 Meaning of Supply Chain Engineering1.3 Supply Chain Decisions1.3.1 Strategic Decisions1.3.2 Tactical Decisions1.3.3 Operational Decisions1.4 Enablers and Drivers of Supply Chain Performance1.4.1 Supply Chain Enablers1.4.2 Supply Chain Drivers1.4.2.1 Inventory1.4.2.2 Transportation1.4.2.3 Facilities1.4.2.4 Suppliers1.4.2.5 Impact of COVID-19 on Supply Chain Drivers1.5 Assessing and Managing Supply Chain Performance1.5.1 Supply Chain Efficiency1.5.2 Supply Chain Responsiveness1.5.3 Supply Chain Risk1.5.4 Conflicting Criteria in Supply Chain Optimization1.6 Relationship between Supply Chain Metrics and Financial Metrics1.6.1 Inventory Measures1.6.1.1 Inventory Turns1.6.1.2 Days of Inventory1.6.1.3 Inventory Capital1.6.2 Business Financial Measures1.6.2.1 Return on Assets1.6.2.2 Working Capital1.6.2.3 Cash-to-Cash Cycle1.7 Importance of Supply Chain Management1.7.1 Supply Chain Top 251.7.2 Evolution of Supply Chains1.8 Organization of the Textbook1.8.1 Chapter 2 (Planning Production in Supply Chains)1.8.2 Chapter 3 (Inventory Management Methods and Models)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 (Warehousing and Distribution)1.8.7 Chapter 8 (Managing Risks in Supply Chains)1.8.8 Chapter 9 (Global Supply Chain Management)1.8.9 Chapter 10 (Health and Humanitarian Supply Chains)1.9 Summary and Further Readings1.9.1 Summary1.9.2 Further ReadingsExercisesReferences
Chapter 2 Planning Production in Supply Chains
2.1 Role of Demand Forecasting in Supply Chain Management2.2 Forecasting Process2.3 Qualitative Forecasting Methods2.3.1 Executive Committee Consensus2.3.2 Delphi Method2.3.3 Survey of Sales Force2.3.4 Customer Surveys2.4 Quantitative Forecasting Methods2.4.1 Time Series Forecasting2.4.2 Constant Level Forecasting Methods2.4.3 Last Value Method2.4.4 Averaging Method2.4.5 Simple Moving Average Method2.4.6 Weighted Moving Average Method2.4.7 Computing Optimal Weights by Linear Programming Model2.4.8 Exponential Smoothing Method2.5 Incorporating Seasonality in Forecasting2.6 Incorporating Trend in Forecasting2.6.1 Simple Linear Trend Model2.6.2 Holt’s Method2.7 Incorporating Seasonality and Trend in Forecasting2.7.1 Method Using Static Seasonality Indices2.7.2 Winters’ Method2.8 Forecasting for Multiple Periods2.8.1 Multi-Period Forecasting under Constant Level2.8.2 Multi-Period Forecasting with Seasonality2.8.3 Multi-Period Forecasting with Trend2.8.4 Multi-Period Forecasting with Seasonality and Trend2.9 Forecasting Errors2.10 Monitoring Forecast Accuracy2.11 Forecasting Software2.11.1 Types of Forecasting Software2.11.2 User Experience with Forecasting Software2.12 Forecasting in Practice2.12.1 Real-World Applications2.12.2 Forecasting in Practice: Survey Results2.13 Production Planning Process2.14 Aggregate Planning Problem2.15 Linear Programming Model for Aggregate Planning2.16 Nonlinear Programming Model for Aggregate Planning2.17 Aggregate Planning as a Transportation Problem2.17.1 Basic Transportation Problem2.17.2 Aggregate Planning as a Transportation Problem2.17.3 Greedy Algorithm for Aggregate Planning2.18 Aggregate Planning Strategies: A Comparison2.19 Summary and Further Readings2.19.1 Demand Forecasting: Summary2.19.2 ARIMA Method2.19.3 Croston’s Method2.19.4 Further Readings in Forecasting2.19.5 Production Planning: Further Readings2.19.6 Managing Demand2.19.7 Bullwhip Effect2.19.8 Collaborative Planning, Forecasting, and Replenishment (CPFR)ExercisesReferences
Chapter 3 Inventory Management Methods and Models
3.1 Decision Framework for Inventory Management3.2 Some Preliminary Modeling Issues3.2.1 Two Critical Tasks3.2.2 ABC Analysis3.3 Single-Item, Single-Period Problem: The Newsvendor3.3.1 Service Measures in Inventory Models3.3.2 Service Impact of Shortage Costs3.3.3 Safety Stock: A First Look3.4 Single-Item, Multi-Period Problems3.4.1 Continuous-Review: Reorder Point–Order Quantity Model3.4.2 Continuous-Review under Uncertainty3.4.3 Periodic-Review, Reorder-Point– Order-Up-To Models3.4.4 Other Periodic-Review Inventory Models3.4.5 Non-Stationary Demand: Distribution Requirements Planning3.5 Multi-Item Inventory Models3.6 Multi-Echelon Inventory Systems3.6.1 Centralized versus Decentralized Control3.6.2 Serial Supply Chain with Deterministic Demand and Fixed Ordering Costs3.6.3 Two-Stage Serial System under Decentralized Control3.6.4 Two-Stage Serial System under Centralized Control3.6.5 Serial Supply Chain with Stochastic Demand and Negligible Fixed Ordering Costs3.6.6 Serial Supply Chain with Fixed Costs and Stochastic Demand3.7 Summary and Further Readings3.7.1 Summary3.7.2 Further ReadingsAppendix: The Bullwhip EffectExercisesReferences
Chapter 4 Transportation Decisions in Supply Chain Management
4.1 Introduction4.2 Motor Carrier Freight: Truckload Mode4.2.1 Accounting for Goods in Transit4.3 Stepping Back: Freight Transportation Overview4.4 More General Models of Freight Rates4.5 Building a Rate Model: LTL Service4.5.1 LTL Mode: Building the Inventory Decision Model4.5.2 LTL Mode: Discount from Published Tariff4.6 A More General Rate Model for LTL Service4.7 Beyond Truck Transport: Rail and Air Cargo4.8 International Freight4.9 Summary and Further Readings4.9.1 Summary4.9.2 Further ReadingsExercisesReferences
Chapter 5 Location and Distribution Decisions in Supply Chains
5.1 Modeling with Binary Variables5.1.1 Capital Budgeting Problem5.1.2 Fixed Charge Problem5.1.3 Constraint with Multiple Right-Hand-Side Constants5.1.4 Quantity Discounts5.1.5 Handling Nonlinear Integer Programs5.1.6 Set Covering and Set Partitioning Models5.1.6.1 Set Covering Problem5.1.6.2 Set Partitioning Problem5.1.6.3 Application to Warehouse Location5.2 Supply Chain Network Optimization5.2.1 Warehouse Location5.2.2 Distribution Planning5.2.3 Location-Distribution Problem5.2.4 Location-Distribution with Dedicated Warehouses5.2.5 Supply Chain Network Design5.3 Risk Pooling or Inventory Consolidation5.3.1 Principles of Risk Pooling5.3.2 General Risk Pooling Model5.3.3 Pros and Cons of Risk Pooling5.3.4 Risk Pooling under Demand Uncertainty5.3.5 Risk Pooling Example5.3.6 Practical Uses of Risk Pooling5.4 Continuous Location Models5.4.1 Continuous Location Model: Single Facility5.4.1.1 Gravity Model5.4.1.2 Iterative Method5.4.1.3 Illustrative Example: Gravity Model5.4.1.4 Limitations of Gravity Model5.4.2 Multiple Facility Location5.5 Real-World Applications5.5.1 Multi-National Consumer Products Company5.5.1.1 Case 1: Supply Chain Network Design5.5.1.2 Case 2: Distribution Planning5.5.2 Procter and Gamble (P&G)5.5.3 Ford Motor Company5.5.4 Hewlett-Packard (HP)5.5.5 BMW5.5.6 AT&T5.5.7 United Parcel Service (UPS)5.6 Closed Loop Supply Chains5.7 Service Industry Applications5.8 Summary and Further Readings5.8.1 Summary5.8.2 Further Readings5.8.2.1 Multiple Criteria Models for Network Design5.8.2.2 Risk Pooling5.8.2.3 Facility Location Decisions5.8.2.4 Case StudiesExercisesReferences
Chapter 6 Supplier Selection Models and Methods
6.1 Supplier Selection Problem6.1.1 Introduction6.1.2 Supplier Selection Process6.1.3 In-House or Outsource6.1.4 Chapter Overview6.2 Supplier Selection Methods6.2.1 Sourcing Strategy6.2.2 Criteria for Selection6.2.3 Impact of COVID-19 on the Selection Criteria6.2.4 Pre-Qualification of Suppliers6.2.5 Final Selection6.2.5.1 Single Sourcing Methods6.2.5.2 Multiple Sourcing Methods6.3 Multi-Criteria Ranking Methods for Supplier Selection6.3.1 Ranking of Suppliers6.3.1.1 Case Study 1: Ranking of Suppliers6.3.2 Use of Lp Metric for Ranking Suppliers6.3.2.1 Steps of the L2 Metric Method6.3.3 Rating (Scoring) Method6.3.4 Borda Count6.3.5 Pair-Wise Comparison of Criteria6.3.6 Scaling Criteria Values6.3.6.1 Simple Scaling6.3.6.2 Ideal Value Method6.3.6.3 Simple Linearization (Linear Normalization)6.3.6.4 Use of Lp Norm (Vector Scaling)6.3.6.5 Illustrative Example of Scaling Criteria Values6.3.6.6 Simple Scaling Illustration6.3.6.7 Scaling by Ideal Value Illustration6.3.6.8 Simple Linearization (Linear Normalization) Illustration6.3.6.9 Scaling by Lp Norm Illustration6.3.7 Analytic Hierarchy Process6.3.7.1 Basic Principles of AHP6.3.7.2 Steps of the AHP Model6.3.8 Cluster Analysis6.3.8.1 Procedure for Cluster Analysis6.3.9 Group Decision Making6.3.10 Comparison of Ranking Methods6.4 Multi-Objective Supplier Allocation Model6.4.1 Notations Used in the Model6.4.2 Mathematical Formulation of the Order Allocation Problem6.4.3 Goal Programming Methodology6.4.3.1 General Goal Programming Model6.4.4 Preemptive Goal Programming6.4.5 Non-Preemptive Goal Programming6.4.6 Tchebycheff (Min–Max) Goal Programming6.4.7 Fuzzy Goal Programming6.4.8 Case Study 2: Supplier Order Allocation6.4.8.1 Preemptive Goal Programming Solution6.4.8.2 Non-Preemptive Goal Programming6.4.8.3 Tchebycheff Goal Programming6.4.8.4 Fuzzy Goal Programming6.4.9 Value Path Approach6.4.9.1 Value Path Approach for the Supplier Selection Case Study6.4.9.2 Discussion of Value Path Results6.5 Case Studies6.5.1 Case Study 3: Risk-Adjusted Supplier Selection Model6.5.2 Case Study 4: Supplier Selection with Supply Segmentation and Product Bundling6.5.3 Case Study 5: Multi-objective Supplier Selection Model with Risk Mitigation6.5.4 Case Study 6: Sustainable Supplier Management6.5.5 Case Study 7: Supplier Selection with Product Life Cycle Considerations6.6 Summary and Further Readings6.6.1 Ranking Suppliers6.6.2 Supplier Order Allocation6.6.2.1 Pre-qualification6.6.3 Global Sourcing6.6.4 Supplier RiskExercisesReferences
Chapter 7 Warehousing and Distribution
7.1 Introduction7.2 Warehouse Types and Functions7.3 Warehouse Activity Profiling7.4 Strategies for Optimizing Warehouse Performance7.4.1 Storage7.4.1.1 Storage Area Requirements7.4.1.2 Effective Space Utilization7.4.1.3 Forward Storage Area7.4.2 Order Picking7.4.2.1 Batch Picking7.4.2.2 Zone Picking7.4.2.3 Determining Picking Paths7.4.3 Put-Away7.5 Cross-Docking7.6 Warehouse Automation7.7 Case Studies7.7.1 Case Study 1: Activity Profiling at Lion Inc.7.7.2 Case Study 2: Slotting in an Aisle7.7.3 Case Study 3: Robotic Automation at Lionette Fulfillment7.8 Summary and Further Readings7.8.1 Summary7.8.2 Further ReadingsExercisesReferences
Chapter 8 Managing Risks in Supply Chain
8.1 Supply Chain Risk8.2 Real-World Risk Events and Their Impacts8.2.1 Importance of Supply Chain Risk Management8.3 Sources of Supply Chain Risks8.4 Risk Identification8.5 Risk Assessment8.5.1 Risk Mapping8.5.2 Risk Prioritization8.5.2.1 Risk Priority Numbers8.5.3 A Framework for Assessing Disruption Risk8.5.3.1 Disruption Risk Assessment8.6 Risk Management8.6.1 Risk Management Strategies8.6.2 Developing a Risk Management Plan8.6.3 Risk Mitigation Strategies8.6.3.1 Traditional Strategies8.6.3.2 Flexible Strategies8.7 Best Industry Practices in Risk Management8.7.1 Teradyne Inc.8.7.2 Hewlett-Packard (HP)8.7.3 Federal Express8.7.4 Wal-Mart8.7.5 Johnson and Johnson8.8 Risk Quantification Models8.8.1 Basic Risk Quantification Models8.9 Value-at-Risk (VaR) Models8.9.1 VaR Type Impact Function8.9.2 Generalized Extreme Value Distribution (GEVD) Functions for Risk Impact8.9.3 Estimating GEVD Parameters8.9.4 VaR Occurrence Functions8.9.5 VaR Disruption Risk Function8.9.5.1 Simulation Approach8.9.5.2 VaR Type Occurrence Function8.9.5.3 VaR Type Disruption Risk Function8.10 Miss-the-Target (MtT) Risk Models8.10.1 MtT Type Impact Function8.10.2 MtT Type Occurrence Function8.10.2.1 Gamma Distribution for S-Type8.10.2.2 Beta Distribution for the L-Type8.10.2.3 Generalized Hyperbolic Distribution for N-Type8.10.3 MtT Type Risk Function8.10.3.1 S-Type Risk Function8.10.3.2 L-Type Risk8.10.3.3 N-Type Risk Function8.11 Risk Measures8.12 Combining VaR and MtT Type Risks8.12.1 Combining Different VaR Type or MtT Type Risks from the Same Supplier4318.12.1.1 VaR Type Risk Combination8.12.1.2 MtT-Type Risk Combination8.12.2 Combining the Same VaR Type or MtT Type Risks from Different Suppliers4338.12.2.1 VaR Type Combination8.12.2.2 MtT Type Risk Combination8.12.3 Combining Total VaR Type or MtT Type Risks from All Suppliers8.12.3.1 VaR Type Combination8.12.3.2 MtT Type Combination8.13 Risk Detectability and Risk Recovery8.13.1 Detectability of Disruptive Events8.13.1.1 Some Basic Properties of Markov Chains8.13.1.2 Computing the MFPT Matrix8.13.1.3 Using MFPT in Disruption Risk Quantification8.13.2 A Conceptual Model for Risk Recovery8.13.3 Illustrative Example of Risk Detectability and Recovery8.14 Case Study 1: Multiple Criteria Optimization Models for Supplier Selection Incorporating Risk4418.14.1 Phase 1 Model (Short-Listing Suppliers)8.14.2 Results of Phase 1 Experiments8.14.2.1 Ranking of the Criteria8.14.2.2 Comparison across Methods for the Same DM8.14.2.3 Comparison across DMs for the Same Method8.14.2.4 Individual Supplier Rankings8.14.2.5 Group Supplier Rankings8.14.2.6 Conclusions from Phase I Results8.14.3 Risk-Adjusted Multi-Criteria Optimization Model for Supplier Sourcing (Phase 2)8.14.3.1 Model Objectives8.14.3.2 Model Constraints8.14.4 Solution Methodology8.14.4.1 Preemptive GP Model8.14.4.2 Non-Preemptive GP Model8.14.4.3 Tchebycheff (Min–Max) GP Model8.14.4.4 Fuzzy GP Model8.14.5 Data Description8.14.5.1 MtT Type Risk Calculations8.14.5.2 VaR-Type Risk Calculations8.14.6 Phase 2 Model Results8.14.6.1 Preemptive GP Solution8.14.6.2 Non-Preemptive GP Solution8.14.6.3 Tchebycheff GP Solution8.14.6.4 Fuzzy GP Solution8.14.7 Comparison of Phase 2 Results8.14.8 Discussion of the Results8.15 Summary and Further Readings8.15.1 Summary8.15.1.1 Extensions8.15.2 Literature on Supply Chain Risk Quantification and Management8.15.2.1 Mathematical Models for Supply Chain Risk Quantification and Management8.15.2.2 Conceptual Models for Supply Chain Risk Management4638.15.2.3 Surveys and Case Studies on Supply Chain Risk Management463ExercisesReferences
Chapter 9 Global Supply Chain Management
9.1 History of Globalization9.2 Impacts of Globalization9.2.1 Changes to World Economies9.2.2 Global Products9.2.3 Impact of Globalization in US Manufacturing9.2.4 Risks in Globalization9.3 Managing Global Supply Chains9.3.1 Global Risk Factors9.3.2 Global Supply Chain Strategies9.3.3 Examples of Globalization Strategies9.4 Global Sourcing9.4.1 Benefits and Barriers to Global Sourcing9.4.1.1 Reasons for Global Sourcing9.4.1.2 Barriers to Global Sourcing9.4.2 Issues in Global Sourcing9.4.2.1 Hidden Costs in Global Sourcing9.4.3 Factors Affecting International Supplier Selection9.4.3.1 Financial Issues9.4.3.2 Logistic Issues9.4.3.3 Manufacturing Practices9.4.3.4 Strategic Issues9.4.4 Tools for Global Sourcing9.5 International Logistics9.5.1 Steady Demand9.5.2 High Demand Variability9.6 Building Resilient Global Supply Chains9.6.1 Supply Chain Vulnerability and Resiliency9.6.2 Building Resiliency9.6.2.1 Increasing Safety Inventory9.6.2.2 Shipping Strategies9.6.2.3 Changing Global Sourcing Strategies9.6.2.4 De-globalization9.6.2.5 Vertical Integration of the Supply Chain9.6.3 Optimization Models for Building Supply Chain Resiliency9.6.3.1 Disruption-Free Base Model9.6.3.2 Vulnerability Analysis9.6.3.3 Risk Mitigation Analysis9.7 Designing a Resilient Global Supply Chain: A Case Study9.7.1 Problem Background9.7.2 Model Features9.7.3 Decision Criteria and Risk Assessment9.7.4 Model Results and Managerial Insights9.7.4.1 Results of Profit Maximization Model9.7.4.2 Multi-Criteria Analysis9.8 Summary and Further Readings9.8.1 Summary9.8.2 Further ReadingsExercisesQuestionsReferences
Chapter 10 Health and Humanitarian Supply Chains
10.1 Introduction10.2 Healthcare Supply Chains10.3 Healthcare Facility Location10.3.1 Location of Emergency Center Facilities10.3.2 Location of Non-Emergency Facilities10.3.3 Special Considerations for Healthcare Facility Location10.4 Capacity Planning and Management10.4.1 Capacity Planning Forecasting10.4.2 Health Resource Management10.4.2.1 Resource Management for Shared Resources10.4.2.2 Workforce Scheduling10.4.2.3 Surge Planning10.5 Telehealth10.6 Humanitarian and Disaster Relief Supply Chains10.6.1 Network Design in Humanitarian Logistics10.6.2 Positioning Inventory for Humanitarian Response10.6.3 Humanitarian Logistics Challenges10.7 Case Studies10.7.1 Case Study 1: Location of Federally Qualified Health Centers10.7.2 Case Study 2: Humanitarian Network Design10.8 Summary and Further Reading10.8.1 Summary10.8.2 Further ReadingExercisesExtended ExercisesReferences
Appendix A: Multiple Criteria Decision Making: An Overview
Index

Content preview from Supply Chain Engineering, 2nd Edition

2 Planning Production in Supply Chains

DOI: 10.1201/9781003283393-2

The success of a manufacturing supply chain depends on its ability to accurately forecast customer demands and produce in time to meet those demands. Thus, forecasting is the starting point for most supply chain management decisions. Based on the demand forecasts, aggregate production planning is done to plan production. Distribution and allocation of resources (equipment, labor, etc.), called material requirements planning, generally follows an aggregate production plan. In this chapter, we will discuss commonly practiced forecasting methods in industry and quantitative models for aggregate production planning.

2.1 Role of Demand Forecasting in Supply Chain Management

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Supply Chain Engineering, 2nd Edition

by A. Ravi Ravindran, Donald P. Warsing, Jr., Paul M. Griffin

2 Planning Production in Supply Chains

2.1 Role of Demand Forecasting in Supply Chain Management

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.