research-article

Dedication load based dispatching rule for photolithography machines with dedication constraint

Authors:

Byung H. KimAuthors Info & Claims

WSC '16: Proceedings of the 2016 Winter Simulation Conference

Pages 2731 - 2739

Published: 11 December 2016 Publication History

Abstract

This paper addresses a semiconductor wafer fabrication (FAB) scheduling problem with dedication constraint. Under dedication constraint, a fabrication lot must be processed using the same photo machine at all photolithography (photo) steps. To solve the utilization decrease of photo machines by dedication, we propose a dedication load as the sum of the workload of lots dedicated to each photo machine. When a photo machine becomes available to process a new lot, if its dedication load is less than the average of similar machines, then the photo machine will be assigned to process the first step of a new lot in the event that one is available. To prove the performance of this proposed dispatching rule, we developed a simulation model based on MIMAC6, and conducted a simulation by using MOZART®. The proposed dispatching rule was implemented and outperformed conventional dispatching rules.

References

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Cited By

Hassoun MKalir A(2017)Towards a new simulation testbed for semiconductor manufacturingProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242495(1-12)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242495
Cho KChung YChoung YPark SKim B(2017)Two boundary based dispatching rule for on-time delivery and throughput of wafer fabs with dedication constraintsProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242490(1-10)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242490

Dedication load based dispatching rule for photolithography machines with dedication constraint
1. Applied computing
2. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning

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Published In

cover image ACM Conferences

WSC '16: Proceedings of the 2016 Winter Simulation Conference

December 2016

3974 pages

ISBN:9781509044849

General Chair:
Todd Huschka
Mayo Clinic
,
Program Chair:
Stephen E. Chick
INSEAD

Sponsors

IIE: Institute of Industrial Engineers
INFORMS-SIM: Institute for Operations Research and the Management Sciences: Simulation Society
SIGSIM: ACM Special Interest Group on Simulation and Modeling
SCS: Society for Modeling and Simulation International

In-Cooperation

SAS
AnyLogic: The AnyLogic Company
Palgrave: Palgrave Macmillan
FlexSim: FlexSim Software Products, Inc.
ASA: American Statistical Association
IEEE/SMC: Institute of Electrical and Electronics Engineers: Systems, Man, and Cybernetics Society
Simio: Simio LLC
ODU: Old Dominion University
ASIM: Arbeitsgemeinschaft Simulation
ExtendSim: ExtendSim
NIST: National Institute of Standards & Technology
Amazon Simulations: Amazon Simulations

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IEEE Press

Publication History

Published: 11 December 2016

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WSC '16

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IIE
INFORMS-SIM
SIGSIM
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WSC '16: Winter Simulation Conference

December 11 - 14, 2016

Virginia, Arlington

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Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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Cited By

Hassoun MKalir A(2017)Towards a new simulation testbed for semiconductor manufacturingProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242495(1-12)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242495
Cho KChung YChoung YPark SKim B(2017)Two boundary based dispatching rule for on-time delivery and throughput of wafer fabs with dedication constraintsProceedings of the 2017 Winter Simulation Conference10.5555/3242181.3242490(1-10)Online publication date: 3-Dec-2017
https://dl.acm.org/doi/10.5555/3242181.3242490

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