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Scenario-based multi-objective robust scheduling for a semiconductor production line

机译:半导体生产线基于场景的多目标鲁棒调度

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Scheduling problems of semiconductor manufacturing systems (SMS) with the goal of optimising some classical performance indices (NP-hard), tend to be increasingly complicated due to stochastic uncertainties. This paper targets the robust scheduling problem of an SMS with uncertain processing times. A three-stage multi-objective robust optimisation (MORO) approach is proposed, that can collaboratively optimise the performance indices and their robustness measures. In the first stage, this paper studies the scheduling problem in the deterministic environment and obtains feasible scheduling strategies that perform well in four performance indices (the average cycle time (CT), the on-time delivery rate (ODR), the throughput (TP), and the total movement amount of wafers (MOV)). Then, in the second stage, the uncertainties are introduced into the production system. In the third stage, this paper proposes a hybrid method consisting of scenario planning, discrete simulation, and multi-objective optimisation to obtain an approximately and more robust optimal solution from the feasible scheduling strategy set. The proposed MORO approach is tested in a semiconductor experiment production line and makes a full analysis to illustrate the effectiveness of our method. The results show that our MORO is superior concerning the total robustness with multi-objective.
机译:由于随机不确定性,以优化一些经典性能指标(NP-hard)为目标的半导体制造系统(SMS)的调度问题往往变得越来越复杂。本文针对具有不确定处理时间的SMS的鲁棒调度问题。提出了一种三阶段的多目标鲁棒优化(MORO)方法,可以协同优化性能指标及其鲁棒性度量。在第一阶段,本文研究确定性环境中的调度问题,并获得可行的调度策略,该策略在四个性能指标(平均周期时间(CT),准时交付率(ODR),吞吐量(TP))中表现良好),以及晶圆的总移动量(MOV))。然后,在第二阶段,将不确定性引入生产系统。在第三阶段,本文提出了一种混合方案,包括方案规划,离散仿真和多目标优化,以从可行的调度策略集中获得近似且更可靠的最优解决方案。提出的MORO方法在半导体实验生产线中进行了测试,并进行了全面分析,以说明我们方法的有效性。结果表明,在具有多目标的总鲁棒性方面,我们的MORO优越。

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