Estimation of percentiles of cycle time in manufacturing simulation

Feng Yang; Bruce E. Ankenman; Barry L. Nelson

doi:10.1109/WSC.2005.1574285

Estimation of percentiles of cycle time in manufacturing simulation

Feng Yang^*, Bruce E. Ankenman, Barry L. Nelson

^*Corresponding author for this work

Industrial Engineering and Management Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

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.

Original language	English (US)
Title of host publication	Proceedings of the 2005 Winter Simulation Conference
Pages	475-484
Number of pages	10
DOIs	https://doi.org/10.1109/WSC.2005.1574285
State	Published - 2005
Event	2005 Winter Simulation Conference - Orlando, FL, United States Duration: Dec 4 2005 → Dec 7 2005

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	2005
ISSN (Print)	0891-7736

Other

Other	2005 Winter Simulation Conference
Country	United States
City	Orlando, FL
Period	12/4/05 → 12/7/05

ASJC Scopus subject areas

Software
Modeling and Simulation
Computer Science Applications

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title = "Estimation of percentiles of cycle time in manufacturing simulation",

abstract = "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.",

author = "Feng Yang and Ankenman, {Bruce E.} and Nelson, {Barry L.}",

year = "2005",

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T1 - Estimation of percentiles of cycle time in manufacturing simulation

AU - Yang, Feng

AU - Ankenman, Bruce E.

AU - Nelson, Barry L.

PY - 2005

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N2 - 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.

AB - 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.

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DO - 10.1109/WSC.2005.1574285

M3 - Conference contribution

AN - SCOPUS:33846685966

SN - 0780395204

SN - 9780780395206

T3 - Proceedings - Winter Simulation Conference

SP - 475

EP - 484

BT - Proceedings of the 2005 Winter Simulation Conference

T2 - 2005 Winter Simulation Conference

Y2 - 4 December 2005 through 7 December 2005

ER -

Estimation of percentiles of cycle time in manufacturing simulation

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