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D-Optimal Sequential Experiments for Generating a Simulation-Based Cycle Time-Throughput Curve

Department of Industrial Engineering, Arizona State University, Tempe, Arizona 85287-5906
Department of Industrial Engineering, Arizona State University, Tempe, Arizona 85287-5906
Department of Industrial Engineering, Arizona State University, Tempe, Arizona 85287-5906
Department of Industrial Engineering, Arizona State University, Tempe, Arizona 85287-5906
Department of Industrial Engineering, Arizona State University, Tempe, Arizona 85287-5906
smpark99{at}yahoo.com
john.fowler{at}asu.edu
mackulak{at}asu.edu
jbert_k{at}yahoo.com
mcarlyle{at}asu.edu

A cycle time-throughput curve quantifies the relationship of average cycle time to throughput rates in a manufacturing system. Moreover, it indicates the asymptotic capacity of a system. Such a curve is used to characterize system performance over a range of start rates. Simulation is a fundamental method for generating such curves since simulation can handle the complexity of real systems with acceptable precision and accuracy. A simulation-based cycle time-throughput curve requires a large amount of simulation output data; the precision and accuracy of a simulated curve may be poor if there is insufficient simulation data. To overcome these problems, sequential simulation experiments based on a nonlinear D-optimal design are suggested. Using the nonlinear shape of the curve, such a design pinpoints p starting design points, and then sequentially ranks the remaining n – p candidate design points, where n is the total number of possible design points being considered. A model of a semiconductor wafer fabrication facility is used to validate the approach. The sequences of experimental runs generated can be used as references for simulation experimenters.

Subject classifications: Simulation: efficient estimation of cycle time-throughput curves. Queues: simulation of queueing networks.
History: Received December 2000; revision received July 2001; accepted July 2001.

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