On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events

Minho Lee; James R. Morrison; Adar A. Kalir; Kosta Rozen

doi:10.1109/COASE.2017.8256191

On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events

Minho Lee
, James R. Morrison
, Adar A. Kalir
, Kosta Rozen

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

Abstract

Preventive Maintenance activities (PMs) are essential for semiconductor manufacturing equipment. Since PMs are typically non-preemptive, they are usually modeled as high priority customers. We examine the accuracy of a popular approximation for the mean cycle time in G/G/1 queues with high priority PM customers. This approximation follows Kingman's and is based on a heavy traffic assumption. We observe that the approximations can perform very poorly when the mean and coefficient of variation of the PM durations are large and small, respectively. This is precisely the practical case for PMs in semiconductor manufacturing. We propose two practical correction candidates and assess their effectiveness. SPECIAL SESSION CODE = 4yd3b.

Original language	English
Title of host publication	2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017
Publisher	Institute of Electrical and Electronics Engineers
Pages	737-738
Number of pages	2
ISBN (Electronic)	9781509067800
DOIs	https://doi.org/10.1109/COASE.2017.8256191
State	Published - 1 Jul 2017
Externally published	Yes
Event	13th IEEE Conference on Automation Science and Engineering, CASE 2017 - Xi'an, China Duration: 20 Aug 2017 → 23 Aug 2017

Publication series

Name	IEEE International Conference on Automation Science and Engineering
Volume	2017-August
ISSN (Print)	2161-8070
ISSN (Electronic)	2161-8089

Conference

Conference	13th IEEE Conference on Automation Science and Engineering, CASE 2017
Country/Territory	China
City	Xi'an
Period	20/08/17 → 23/08/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/COASE.2017.8256191

Cite this

Lee, M., Morrison, J. R., Kalir, A. A., & Rozen, K. (2017). On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events. In 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017 (pp. 737-738). (IEEE International Conference on Automation Science and Engineering; Vol. 2017-August). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/COASE.2017.8256191

Lee, Minho ; Morrison, James R. ; Kalir, Adar A. et al. / On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events. 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. Institute of Electrical and Electronics Engineers, 2017. pp. 737-738 (IEEE International Conference on Automation Science and Engineering).

@inproceedings{0ecdec2005424815940d2c4c33a7466f,

title = "On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events",

abstract = "Preventive Maintenance activities (PMs) are essential for semiconductor manufacturing equipment. Since PMs are typically non-preemptive, they are usually modeled as high priority customers. We examine the accuracy of a popular approximation for the mean cycle time in G/G/1 queues with high priority PM customers. This approximation follows Kingman's and is based on a heavy traffic assumption. We observe that the approximations can perform very poorly when the mean and coefficient of variation of the PM durations are large and small, respectively. This is precisely the practical case for PMs in semiconductor manufacturing. We propose two practical correction candidates and assess their effectiveness. SPECIAL SESSION CODE = 4yd3b.",

author = "Minho Lee and Morrison, \{James R.\} and Kalir, \{Adar A.\} and Kosta Rozen",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 13th IEEE Conference on Automation Science and Engineering, CASE 2017 ; Conference date: 20-08-2017 Through 23-08-2017",

year = "2017",

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doi = "10.1109/COASE.2017.8256191",

language = "English",

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Lee, M, Morrison, JR, Kalir, AA & Rozen, K 2017, On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events. in 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. IEEE International Conference on Automation Science and Engineering, vol. 2017-August, Institute of Electrical and Electronics Engineers, pp. 737-738, 13th IEEE Conference on Automation Science and Engineering, CASE 2017, Xi'an, China, 20/08/17. https://doi.org/10.1109/COASE.2017.8256191

On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events. / Lee, Minho; Morrison, James R.; Kalir, Adar A. et al.
2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. Institute of Electrical and Electronics Engineers, 2017. p. 737-738 (IEEE International Conference on Automation Science and Engineering; Vol. 2017-August).

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

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N2 - Preventive Maintenance activities (PMs) are essential for semiconductor manufacturing equipment. Since PMs are typically non-preemptive, they are usually modeled as high priority customers. We examine the accuracy of a popular approximation for the mean cycle time in G/G/1 queues with high priority PM customers. This approximation follows Kingman's and is based on a heavy traffic assumption. We observe that the approximations can perform very poorly when the mean and coefficient of variation of the PM durations are large and small, respectively. This is precisely the practical case for PMs in semiconductor manufacturing. We propose two practical correction candidates and assess their effectiveness. SPECIAL SESSION CODE = 4yd3b.

AB - Preventive Maintenance activities (PMs) are essential for semiconductor manufacturing equipment. Since PMs are typically non-preemptive, they are usually modeled as high priority customers. We examine the accuracy of a popular approximation for the mean cycle time in G/G/1 queues with high priority PM customers. This approximation follows Kingman's and is based on a heavy traffic assumption. We observe that the approximations can perform very poorly when the mean and coefficient of variation of the PM durations are large and small, respectively. This is precisely the practical case for PMs in semiconductor manufacturing. We propose two practical correction candidates and assess their effectiveness. SPECIAL SESSION CODE = 4yd3b.

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M3 - Conference contribution

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Lee M, Morrison JR, Kalir AA, Rozen K. On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events. In 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. Institute of Electrical and Electronics Engineers. 2017. p. 737-738. (IEEE International Conference on Automation Science and Engineering). doi: 10.1109/COASE.2017.8256191

On the accuracy of analytic approximations for the mean cycle time in semiconductor manufacturing equipment with PM events

Abstract

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Conference

UN SDGs

ASJC Scopus subject areas

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