Objects. The ~ b s t rac t ~ b j ect forms the fundamental base class for the entire design and all other classes are derived from this base class. The Abstract Object class defines and characterizes all the essential properties every class in this 404 OBJECT-ORIENTED SIMULATION

Handbook of Simulation

Power grids, flexible manufacturing, cellular communications: interconnectedness has consequences. This remarkable book gives the tools and philosophy you need to build network models detailed enough to capture essential dynamics but simple enough to expose the structure of effective control solutions and to clarify analysis. Core chapters assume only exposure to stochastic processes and linear algebra at the undergraduate level; later chapters are for advanced graduate students and researchers/practitioners. This gradual development bridges classical theory with the state-of-the-art. The workload model that is the basis of traditional analysis of the single queue becomes a foundation for workload relaxations used in the treatment of complex networks. Lyapunov functions and dynamic programming equations lead to the celebrated MaxWeight policy along with many generalizations. Other topics include methods for synthesizing hedging and safety stocks, stability theory for networks, and techniques for accelerated simulation. Examples and figures throughout make ideas concrete. Solutions to end-of-chapter exercises available on a companion website.

http://www.meyn.ece.ufl.edu/archive/spm_files/Presentations/Atlanta05.pdf

Control Techniques for Complex Networks

In the first part of this review [62] we described the characteristics of semiconductor manufacturing environments and reviewed research on system performance evaluation and production planning. In this paper we focus on shop-floor control problems. We classify research to date by the solution techniques used, and discuss the relative advantages and disadvantages of the various approaches. We discuss the relationship between shop-floor control and production planning and suggest future research directions.

A review of production planning and scheduling models in the semiconductor industry part ii: shop-floor control

Control: A perspective

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.- References.- 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.- Related Bibliography on Phase-Type Distributions.- References.- Problems.- 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.- Related Literature.- References.- Problems.- 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.- Related Literature.- References.- Problems.- 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.- Related Bibliography.- References.- Problems.- 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.- Related Bibliography.- References.- Problems.- 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.- Related Bibliography.- References.- Problems.- Appendix: A Single-Stage P/I System with PH Delay, Set-up, and Processing Times.

Performance analysis of manufacturing systems

The problem of reducing the mean and variance of cycle time in semiconductor manufacturing plants is addressed. Such plants feature a characteristic reentrant process flow, where lots repeatedly return at different stages of their production to the same service stations for further processing, consequently creating much competition for machines. We introduce a new class of scheduling policies, called Fluctuation Smoothing policies. Unanimously, our policies achieved the best mean cycle time and Standard Deviation of Cycle Time, in all the configurations of plant models and release policies tested. As an example, under the recommended Workload Regulation Release policy, for a heavily loaded Research and Development Fabrication Line model, our Fluctuation Smoothing policies achieved a reduction of 22.4% in the Mean Queueing Time, and a reduction of 52.0% in the Standard Deviation of Cycle Time, over the baseline FIFO policy. These conclusions are based on extensive simulations conducted on two models of semiconductor manufacturing plants. The first is a model of a Research and Development Fabrication Line. The second is an aggregate model intended to approximate a full scale production line. Statistical tests are used to corroborate our conclusions. >

Efficient scheduling policies to reduce mean and variance of cycle-time in semiconductor manufacturing plants

We address the problem of scheduling semiconductor manufacturing plants. The goal is to choose the lot release policy and the job scheduling policy so as to reduce the mean and variance of cycle-time. We introduce a new class of scheduling policies, called Fluctuation Smoothing policies. We have tested our policies on two models of semiconductor manufacturing plants. The first is the research and development fabrication line that has been examined earlier by Wein [ 5 ] . The second is an approximate model of a full scale production line. In comparison with our policies, the best previously known policies yield a 12.5% worse mean cycle-time, and a 45% worse standard deviation of cycle-time, on average. Statistical tests corroborate our conclusions.

S.C.H. Lu

Papers

Efficient scheduling policies to reduce mean and variance of cycle-time in semiconductor manufacturing plants

Scheduling Semiconductor Manufacturing Plants to Reduce Mean and Variance of Cycle-Time