An Evaluation of Strategies for Job Mix Selection in Job Shop Production Environments - Case: A Photolithography Workstation
引用次数: 2
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.作业车间生产环境中作业组合选择策略的评估-以光刻工作站为例
本研究考察了作业车间生产环境中各生产班次中工作组合选择的影响。这是半导体制造系统中光刻工作站的一个关键问题。为此，本文提出了一种基于进化学习的仿真优化(ELBSO)方法，用于解决从实际半导体制造数据集中捕获的一组随机作业车间调度问题。实验结果表明，当机器在处理不同的作业操作方面具有灵活性，并且某一班次所选择的作业的交货期尽可能相等时，每个班次的性能最佳。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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