Manufacturing industries are devoted to producing high-quality products in the most economical and timely manner. Quality, economics, and time not only indicate the customer-satisfaction level, but also measure the manufacturing per­ formance of a company. Today's manufacturing environments are becoming more and more complex, flexible, and information-intensive. Companies invest into the information technologies such as computers, communication networks, sensors, actuators, and other equipment that give them an abundance of information about their materials and resources. In the face of global competition, a manufacturing company's survival is becoming more dependent on how best this influx of in­ formation is utilized. Consequently, there evolves a great need for sophisticated tools of performance analysis that use this information to help decision makers in choosing the right course of action. These tools will have the capability of data analysis, modeling, computer simulation, and optimization for use in designing products and processes. International competition also has had its impact on manufacturing education and the government's support of it in the US. We see more courses offered in this area in industrial engineering and manufacturing systems engineering departments, operations research programs, and business schools. In fact, we see an increasing number of manufacturing systems engineering departments and manufacturing research centers in universities not only in the US but also in Europe, Japan, and many developing countries.

1. Introduction to the Modeling of Manufacturing Systems.- 1.1. Typical Decision Problems in Manufacturing Systems.- 1.2. Performance Evaluation.- 1.3. Models of Manufacturing Systems.- 1.4. Design of Manufacturing Systems.- 2. Tools of Probability.- 2.1. Random Variables and Their Distributions.- 2.2. Joint Distributions.- 2.3. Conditional Distributions.- 2.4. Functions of Random Variables.- 2.5. Moments of Random Variables.- 2.6. Special Distributions.- 2.7. Stochastic Processes.- 2.8. Phase-Type Distributions.- 3. Analysis of Single Work Stations.- 3.1. Introduction.- 3.2. A Simple Work Station.- 3.3. Distribution of the Number in the System.- 3.4. Work Stations Subject to Failures.- 3.5. Distribution of the Number of Jobs in a Work Station Subject to Failures.- 3.6. The Process-Completion Time.- 3.7. Failure-Repair Policies.- 3.8. The Machine Interference Problem.- 4. Analysis of Flow Lines.- 4.1. Introduction.- 4.2. Characteristics of Flow Lines.- 4.3. Analysis of Two-Station Flow Lines.- 4.4. Analysis of Flow Lines With More Than Two Stations.- 4.5. Deterministic Processing Times.- 4.6. Bounds on the Output Rate.- 4.7. Design Problems in Flow Lines.- 5. Analysis of Transfer Lines.- 5.1. Introduction.- 5.2. A Two-Station Line with No Intermediate Buffer: A Regenerative Approach.- 5.3. Transfer Lines with Work-in-Process Buffers.- 5.4. Buffer Clearing Policies in Transfer Lines.- 5.5. Analysis of a Two-Machine Synchronous Line Under BCP1.- 5.6. Operation Under BCP2.- 5.7. Line Behavior and Design Issues.- 5.8. Analysis of Larger Systems.- 5.9. Transfer Lines with No Scrapping.- 6. Assembly Systems.- 6.1. Introduction.- 6.2. An Asynchronous Assembly System.- 6.3. Approximate Analysis of the Two-Station Assembly System.- 6.4. Analysis of Larger Systems.- 6.5. Synchronous Assembly Systems.- 6.6. Relaxing the Assembly Assumption.- 7. Pull-Type Manufacturing Systems.- 7.1. Introduction.- 7.2. Production Control Policies.- 7.3. Analysis of Single-Stage, Single-Product Systems.- 7.4. A Single-Stage System with Two Products.- 7.5. Multistage Pull-Type Systems.- 7.6. The Generalized Kanban Scheme.- 7.7. Manufacturing Systems with Inventory Procurement.- 7.8. A Two-Stage, MultiProduct System.- 7.9. The Look-Back Policy.