An Application of Adaptive Genetic Algorithm Combining Monte Carlo Method

Wei Yu, Xu Chen, Jing-fen Lu, Zhengying Wei
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Abstract

Over the past decades, semiconductor manufacturing has been drawing more and more attention. The procedures it involves could be considered as one of the most complicated processes in manufacturing. Owing to this, cases caused by abnormal machines happened from time to time. It requires a large amount of time and experience to solve this problem manually. Meanwhile, state of machines changes as time goes by. As a result, engineers are expected to find out root causes as soon as possible. In this paper, adaptive genetic algorithm is introduced to identify common bad tools and provide suggestions for case study.
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自适应遗传算法结合蒙特卡罗方法的应用
在过去的几十年里,半导体制造引起了越来越多的关注。它所涉及的程序可以被认为是制造业中最复杂的过程之一。因此,机器异常引起的情况时有发生。手动解决这个问题需要大量的时间和经验。同时,机器的状态随着时间的推移而变化。因此,工程师应该尽快找出根本原因。本文引入自适应遗传算法来识别常见的不良工具,并为案例研究提供建议。
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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