An Evaluation of Strategies for Job Mix Selection in Job Shop Production Environments-Case: A Photolithography Workstation

Amir Ghasemi, Cathal Heavey

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this research the impact of job mix selection in each production shift in a job shop production environment is examined. This is a critical question within photolithography workstations in semiconductor manufacturing systems. For this purpose, a recently developed Simulation Optimization (SO) method named Evolutionary Learning Based Simulation Optimization (ELBSO) is implemented to solve a set of designed Stochastic Job Shop Scheduling problems captured from a real semiconductor manufacturing data set. Experiment results indicate that the best performance in each shift occurs when machines are flexible in terms of processing different job operations, and the selected jobs for a certain shift have as equal as possible due dates.

Original languageEnglish
Title of host publication2021 Winter Simulation Conference, WSC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433112
DOIs
Publication statusPublished - 2021
Event2021 Winter Simulation Conference, WSC 2021 - Phoenix, United States
Duration: 12 Dec 202115 Dec 2021

Publication series

NameProceedings - Winter Simulation Conference
Volume2021-December
ISSN (Print)0891-7736

Conference

Conference2021 Winter Simulation Conference, WSC 2021
Country/TerritoryUnited States
CityPhoenix
Period12/12/2115/12/21

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