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Supply chain engineering : models and applications / A. Ravi Ravindran, Donald P. Warsing, Jr.

Author
Ravindran, A., 1944-
Published
Boca Raton, FL : Taylor & Francis, 2012.
Physical Description
xxiv 521 pages : illustrations ; 24 cm.
Additional Creators
Warsing, Donald Paul

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Contents
Machine generated contents note: 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) -- 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 -- 2.Planning Production in Supply Chains -- 2.1.Role of Demand Forecasting in Supply Chain Management -- 2.2.Forecasting Process -- 2.3.Qualitative Forecasting Methods -- 2.3.1.Executive Committee Consensus -- 2.3.2.Delphi Method -- 2.3.3.Survey of Sales Force -- 2.3.4.Customer Surveys -- 2.4.Quantitative Forecasting Methods -- 2.4.1.Time Series Forecasting -- 2.4.2.Constant Level Forecasting Methods -- 2.4.3.Last Value Method -- 2.4.4.Averaging Method -- 2.4.5.Simple Moving Average Method -- 2.4.6.Weighted Moving Average Method -- 2.4.7.Computing Optimal Weights by Linear Programming Model -- 2.4.8.Exponential Smoothing Method -- 2.5.Incorporating Seasonally in Forecasting -- 2.6.Incorporating Trend in Forecasting -- 2.6.1.Simple Linear Trend Model -- 2.6.2.Holt's Method -- 2.7.Incorporating Seasonality and Trend in Forecasting -- 2.7.1.Method Using Static Seasonality Indices -- 2.7.2.Winters' Method -- 2.8.Forecasting for Multiple Periods -- 2.8.1.Multi-Period Forecasting under Constant Level -- 2.8.2.Multi-Period Forecasting with Seasonality -- 2.8.3.Multi-Period Forecasting with Trend -- 2.8.4.Multi-Period Forecasting with Seasonality and Trend -- 2.9.Forecasting Errors -- 2.10.Monitoring Forecast Accuracy -- 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 -- 3.5.Multi-Item Inventory Models -- 3.6.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 -- 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 -- 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 -- 5.1.5.Handling Nonlinear Integer Programs -- 5.1.6.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 -- 6.Supplier Selection Models and Methods -- 6.1.Supplier Selection Problem -- 6.1.1.Introduction -- 6.1.2.Supplier Selection Process -- 6.1.3.In-House or Outsource -- 6.1.4.Chapter Overview -- 6.2.Supplier Selection Methods -- 6.2.1.Sourcing Strategy -- 6.2.2.Criteria for Selection -- 6.2.3.Pre-Qualification of Suppliers -- 6.2.4.Final Selection -- 6.2.4.1.Single Sourcing Methods -- 6.2.4.2.Multiple Sourcing Methods -- 6.3.Multi-Criteria Ranking Methods for Supplier Selection -- 6.3.1.Ranking of Suppliers -- 6.3.1.1.Case Study 1: Ranking of Suppliers -- 6.3.2.Use of Lp Metric for Ranking Suppliers -- 6.3.2.1.Steps of the L2 Metric Method -- 6.3.3.Rating (Scoring) Method -- 6.3.4.Borda Count -- 6.3.5.Pair-Wise Comparison of Criteria -- 6.3.6.Scaling Criteria Values -- 6.3.6.1.Simple Scaling -- 6.3.6.2.Ideal Value Method -- 6.3.6.3.Simple Linearization (Linear Normalization) -- 6.3.6.4.Use of Lp Norm (Vector Scaling) -- 6.3.6.5.Illustrative Example of Scaling Criteria Values -- 6.3.6.6.Simple Scaling Illustration -- 6.3.6.7.Scaling by Ideal Value Illustration -- 6.3.6.8.Simple Linearization (Linear Normalization) Illustration -- 6.3.6.9.Scaling by Lp Norm Illustration -- 6.3.7.Analytic Hierarchy Process -- 6.3.7.1.Basic Principles of AHP -- 6.3.7.2.Steps of the AHP Model -- 6.3.8.Cluster Analysis -- 6.3.8.1.Procedure for Cluster Analysis -- 6.3.9.Group Decision Making -- 6.3.10.Comparison of Ranking Methods -- 6.4.Multi-Objective Supplier Allocation Model -- 6.4.1.Notations Used in the Model -- 6.4.2.Mathematical Formulation of the Order Allocation Problem -- 6.4.3.Goal Programming Methodology -- 6.4.3.1.General Goal Programming Model -- 6.4.4.Preemptive Goal Programming -- 6.4.5.Non-Preemptive Goal Programming -- 6.4.6.Tchebycheff (Min-Max) Goal Programming -- 6.4.7.Fuzzy Goal Programming -- 6.4.8.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 -- and Contents note continued: 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.Teradyne Inc. -- 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 -- 7.9.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 -- 7.10.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 for N-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 -- 7.11.Risk Measures -- 7.12.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 -- 7.13.Risk Detectability and Risk Recovery -- 7.13.1.Detectability of Disruptive Events -- 7.13.1.1.Some Bask 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 -- 7.14.Multiple Criteria Optimization Models for Supplier Selection Incorporating Risk -- 7.14.1.Phase 1 Model (Short-Listing Suppliers) -- 7.14.2.Results of Phase 1 Experiments -- 7.14.2.1.Ranking of the Criteria -- 7.14.2.2.Comparison across Methods for the Same DM -- 7.14.2.3.Comparison across DMs for the Same Method -- 7.14.2.4.Individual Supplier Rankings -- 7.14.2.5.Group Supplier Rankings -- 7.14.2.6.Conclusions from Phase I Results -- 7.14.3.Risk Adjusted Multi-Criteria Optimization Model for Supplier Sourcing (Phase 2) -- 7.14.3.1.Model Objectives -- 7.14.3.2.Model Constraints -- 7.14.4.Solution Methodology -- 7.14.4.1.Preemptive GP Model -- 7.14.4.2.Non-Preemptive GP Model -- 7.14.4.3.Tchebycheff (Min-Max) GP Model -- 7.14.4.4.Fuzzy GP Model -- 7.14.5.Data Description -- 7.14.5.1.MtT Type Risk Calculations -- 7.14.5.2.VaR Type Risk Calculations -- 7.14.6.Phase 2 Model Results -- 7.14.6.1.Preemptive GP Solution -- 7.14.6.2.Non-Preemptive GP Solution -- 7.14.6.3.Tchebycheff GP Solution -- 7.14.6.4.Fuzzy GP Solution -- 7.14.7.Comparison of Phase 2 Results -- 7.14.8.Discussion of the Results -- 7.15.Summary and Further Readings -- 7.15.1.Summary -- 7.15.1.1.Extensions -- 7.15.2.Literature on Supply Chain Risk Quantification and Management -- 7.15.2.1.Mathematical Models for Supply Chain Risk Quantification and Management -- 7.15.2.2.Conceptual Models for Supply Chain Risk Management -- 7.15.2.3.Surveys and Case Studies on Supply Chain Risk Management -- Exercises -- References -- 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.
Summary
"Preface This book emphasizes a quantitative approach to solving problems related to designing and operating supply chains. Importantly, though, it is not so "micro" in its focus that the perspective on the larger business problems is lost, nor is it so "macro" in its treatment of that business context that it fails to develop students' appreciation for, and skills to solve, the tactical problems that must be addressed in effectively managing flows of goods in supply chains. Economists often speak of the need to understand "first principles" before one can understand and solve larger problems. We share that view, and we have therefore structured the book to provide a grounding in the "first principles" relevant to the broad and challenging problem of managing a supply chain that spans the globe. We feel strongly that students of supply chain engineering are best served by first developing a solid understanding of, and a quantitative toolkit for, tactical decision making in areas such as demand forecasting, inventory management, and transportation management--in both an intrafirm and firm-to-firm (dyadic) context--before making any attempt to "optimize the supply chain," a task that is clearly much easier said than done, or to optimize large swaths of any given supply chain. Still, the idea of optimization is indeed prevalent throughout the book. This book is careful and deliberate in its approach to supply chain optimization. Indeed, the perspective taken is one that is well known to engineers of all types, namely, the perspective of design. Engineers design things. Some engineers design discrete physical items, and some design collections of items that operate together as systems"--
Subject(s)
ISBN
9781439811986 (hardback)
1439811989 (hardback)
Bibliography Note
Includes bibliographical references and index.
Source of Acquisition
Purchased with funds from the J. Harvey Fahnestock Endowment for Scientific, Engineering and Rare Books; 2012
Endowment Note
J. Harvey Fahnestock Endowment for Scientific, Engineering and Rare Books
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