Matching supply with demand : an introduction to operations management

Cover
Matching Supply with Demand: An Introduction to Operations Management
Dedication
About the Authors
Acknowledgements
Preface
Changes to This Edition
Resources for Instructors and Students
Brief Contents
Table of Contents
Chapter 1 Introduction
	1.1 Learning Objectives and Framework
	1.2 Road Map of the Book
Chapter 2 The Process View of the Organization
	2.1 Presbyterian Hospital in Philadelphia
	2.2 Three Measures of Process Performance
	2.3 Little’s Law
	2.4 Inventory Turns and Inventory Costs
	2.5 Five Reasons to Hold Inventory
		Pipeline Inventory
		Seasonal Inventory
		Cycle Inventory
		Decoupling Inventory/Buffers
		Safety Inventory
	2.6 The Product–Process Matrix
Chapter 3 Understanding the Supply Process: Evaluating Process Capacity
	3.1 How to Draw a Process Flow Diagram
	3.2 Bottleneck, Process Capacity, and Flow Rate (Throughput)
	3.3 How Long Does It Take to Produce a Certain Amount of Supply?
	3.4 Process Utilization and Capacity Utilization
	3.5 Workload and Implied Utilization
	3.6 Multiple Types of Flow Units
Chapter 4 Estimating and Reducing Labor Costs
	4.1 Analyzing an Assembly Operation
	4.2 Time to Process a Quantity X Starting with an Empty Process
	4.3 Labor Content and Idle Time
	4.4 Increasing Capacity by Line Balancing
	4.5 Scale Up to Higher Volume
		Increasing Capacity by Replicating the Line
		Increasing Capacity by Selectively Adding Workers
		Increasing Capacity by Further Specializing Tasks
Chapter 5 Batching and Other Flow Interruptions: Setup Times and the Economic Order Quantity Model
	5.1 The Impact of Setups on Capacity
	5.2 Interaction between Batching and Inventory
	5.3 Choosing a Batch Size in the Presence of Setup Times
	5.4 Setup Times and Product Variety
	5.5 Setup Time Reduction
	5.6 Balancing Setup Costs with Inventory Costs: The EOQ Model
	5.7 Observations Related to the Economic Order Quantity
Chapter 6 The Link between Operations and Finance
	6.1 Paul Downs Cabinetmakers
	6.2 Building an ROIC Tree
	6.3 Valuing Operational Improvements
	6.4 Analyzing Operations Based on Financial Data
Chapter 7 Quality and Statistical Process Control
	7.1 The Statistical Process Control Framework
	7.2 Capability Analysis
		Determining a Capability Index
		Predicting the Probability of a Defect
		Setting a Variance Reduction Target
		Process Capability Summary and Extensions
	7.3 Conformance Analysis
	7.4 Investigating Assignable Causes
	7.5 Defects with Binary Outcomes: p-Charts
	7.6 Impact of Yields and Defects on Process Flow
		Rework
		Eliminating Flow Units from the Process
		Cost Economics and Location of Test Points
		Defects and Variability
	7.7 A Process for Improvement
Chapter 8 Lean Operations and the Toyota Production System
	8.1 The History of Toyota
	8.2 TPS Framework
	8.3 The Seven Sources of Waste
	8.4 JIT: Matching Supply with Demand
		Achieve One-Unit-at-a-Time Flow
		Produce at the Rate of Customer Demand
		Implement Pull Systems
	8.5 Quality Management
	8.6 Exposing Problems through Inventory Reduction
	8.7 Flexibility
	8.8 Standardization of Work and Reduction of Variability
	8.9 Human Resource Practices
	8.10 Lean Transformation
Chapter 9 Variability and Its Impact on Process Performance: Waiting Time Problems
	9.1 Motivating Example: A Somewhat Unrealistic Call Center
	9.2 Variability: Where It Comes From and How It Can Be Measured
	9.3 Analyzing an Arrival Process
		Stationary Arrivals
		Exponential Interarrival Times
		Nonexponential Interarrival Times
		Summary: Analyzing an Arrival Process
	9.4 Processing Time Variability
	9.5 Predicting the Average Waiting Time for the Case of One Resource
	9.6 Predicting the Average Waiting Time for the Case of Multiple Resources
	9.7 Service Levels in Waiting Time Problems
	9.8 Economic Implications: Generating a Staffing Plan
	9.9 Impact of Pooling: Economies of Scale
	9.10 Reducing Variability
		Ways to Reduce Arrival Variability
		Ways to Reduce Processing Time Variability
Chapter 10 The Impact of Variability on Process Performance: Throughput Losses
	10.1 Motivating Examples: Why Averages Do Not Work
	10.2 Ambulance Diversion
	10.3 Throughput Loss for a Simple Process
	10.4 Customer Impatience and Throughput Loss
	10.5 Several Resources with Variability in Sequence
		The Role of Buffers
Chapter 11 Scheduling to Prioritize Demand
	11.1 Scheduling Timeline and Applications
	11.2 Resource Scheduling—Shortest Processing Time
		Performance Measures
		First-Come-First-Served vs. Shortest Processing Time
		Limitations of Shortest Processing Time
	11.3 Resource Scheduling with Priorities—Weighted Shortest Processing Time
	11.4 Resource Scheduling with Due Dates—Earliest Due Date
	11.5 Theory of Constraints
	11.6 Reservations and Appointments
		Scheduling Appointments with Uncertain Processing Times
		No-Shows
Chapter 12 Project Management
	12.1 Motivating Example
	12.2 Critical Path Method
	12.3 Computing Project Completion Time
	12.4 Finding the Critical Path and Creating a Gantt Chart
	12.5 Computing Slack Time
	12.6 Dealing with Uncertainty
		Random Activity Times
		Potential Iteration/Rework Loops
		Decision Tree/Milestones/Exit Option
		Unknown Unknowns
	12.7 How to Accelerate Projects
Chapter 13 Forecasting
	13.1 Forecasting Framework
	13.2 Evaluating the Quality of a Forecast
	13.3 Eliminating Noise from Old Data
		Naïve Model
		Moving Averages
		Exponential Smoothing Method
		Comparison of Methods
	13.4 Time Series Analysis—Trends
	13.5 Time Series Analysis—Seasonality
	13.6 Expert Panels and Subjective Forecasting
		Sources of Forecasting Biases
	13.7 Conclusion
Chapter 14 Betting on Uncertain Demand: The Newsvendor Model
	14.1 O’Neill Inc.
	14.2 The Newsvendor Model: Structure and Inputs
	14.3 How to Choose an Order Quantity
	14.4 Performance Measures
		Expected Leftover Inventory
		Expected Sales
		Expected Lost Sales
		Expected Profit
		In-Stock Probability and Stockout Probability
	14.5 How to Achieve a Service Objective
	14.6 How to Construct a Demand Forecast
	14.7 Managerial Lessons
Chapter 15 Assemble-to-Order, Make-to-Order, and Quick Response with Reactive Capacity
	15.1 Evaluating and Minimizing the Newsvendor’s Demand–Supply Mismatch Cost
	15.2 When Is the Mismatch Cost High?
	15.3 Reducing Mismatch Costs with Make-to-Order
	15.4 Quick Response with Reactive Capacity
Chapter 16 Service Levels and Lead Times in Supply Chains: The Order-up-to Inventory Model
	16.1 Medtronic’s Supply Chain
	16.2 The Order-up-to Model Design and Implementation
	16.3 The End-of-Period Inventory Level
	16.4 Choosing Demand Distributions
	16.5 Performance Measures
		In-Stock and Stockout Probability
		Expected On-Hand Inventory
		Pipeline Inventory/Expected On-Order Inventory
		Expected Back Order
	16.6 Choosing an Order-up-to Level to Meet a Service Target
	16.7 Choosing an Appropriate Service Level
	16.8 Controlling Ordering Costs
	16.9 Managerial Insights
Chapter 17 Risk-Pooling Strategies to Reduce and Hedge Uncertainty
	17.1 Location Pooling
		Pooling Medtronic’s Field Inventory
		Medtronic’s Distribution Center(s)
		Electronic Commerce
	17.2 Product Pooling
	17.3 Lead Time Pooling: Consolidated Distribution and Delayed Differentiation
		Consolidated Distribution
		Delayed Differentiation
	17.4 Capacity Pooling with Flexible Manufacturing
Chapter 18 Revenue Management with Capacity Controls
	18.1 Revenue Management and Margin Arithmetic
	18.2 Protection Levels and Booking Limits
	18.3 Overbooking
	18.4 Implementation of Revenue Management
		Demand Forecasting
		Dynamic Decisions
		Variability in Available Capacity
		Reservations Coming in Groups
		Effective Segmenting of Customers
		Multiple Fare Classes
		Software Implementation
		Variation in Capacity Purchase: Not All Customers Purchase One Unit of Capacity
Chapter 19 Supply Chain Coordination
	19.1 The Bullwhip Effect: Causes and Consequences
		Order Synchronization
		Order Batching
		Trade Promotions and Forward Buying
		Reactive and Overreactive Ordering
		Shortage Gaming
	19.2 The Bullwhip Effect: Mitigating Strategies
		Sharing Information
		Smoothing the Flow of Product
		Eliminating Pathological Incentives
		Using Vendor-Managed Inventory
		The Countereffect to the Bullwhip Effect: Production Smoothing
	19.3 Incentive Conflicts in a Sunglasses Supply Chain
	19.4 Buy-Back Contracts
	19.5 More Supply Chain Contracts
		Quantity Discounts
		Options Contracts
		Revenue Sharing
		Quantity Flexibility Contracts
		Price Protection
Appendix A Statistics Tutorial
Appendix B Tables
Appendix C Evaluation of the Expected Inventory and Loss Functions
Appendix D Equations and Approximations
Appendix E Solutions to Selected Practice Problems
Glossary
References
Index of Key “How to” Exhibits
Summary of Key Notation and Equations
Index