Abstract | ||
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Cycle time-throughput (CT-TH) percentile curves quantify the relationship between percentiles of cycle time and factory throughput, and they can play an important role in strategic planning for manufacturing systems. In this paper, a highly flexible distribution, the generalized gamma, is used to represent the underlying distribution of cycle time. To obtain CT-TH percentile curves, we fit metamodels for the first three CT-TH moment curves throughout the throughput range of interest, determine the parameters of the generalized gamma by matching moments, and obtain percentiles by inverting the distribution. To insure efficiency and control estimation error, simulation experiments are built up sequentially using a multistage procedure. Numerical results are presented to demonstrate the effectiveness of the approach. |
Year | DOI | Venue |
---|---|---|
2005 | 10.1109/WSC.2005.1574285 | Winter Simulation Conference |
Keywords | Field | DocType |
flexible distribution,generalized gamma,highly flexible distribution,cycle time percentiles estimation,cycle time-throughput,strategic planning,manufacturing systems,ct-th moment curve,underlying distribution,gamma distribution,manufacturing simulation,manufacturing system,factory throughput,ct-th percentile curve,cycle time,percentile curve,cycle time-throughput percentile curves,throughput range,simulation experiment | Factory,Simulation,Manufacturing systems,Computer science,Gamma distribution,Throughput,Strategic planning,Percentile | Conference |
ISBN | Citations | PageRank |
0-7803-9519-0 | 3 | 0.55 |
References | Authors | |
3 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Feng Yang | 1 | 47 | 7.21 |
Bruce E. Ankenman | 2 | 145 | 18.19 |
Barry L. Nelson | 3 | 1876 | 257.62 |