Manufacturing modeling and optimization

D. O'Ferrell
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引用次数: 6

Abstract

The purpose of this project was to model and optimize the personnel and equipment utilization in Siltec's Epitaxial manufacturing process. Previous attempts to model the behavior of the process through static models (linear programming and spreadsheets) had not attempted to explain any of the variability experienced in the process line. SIMAN was used to create a simple model to study the effects of crosstraining on productivity and cycle time. The model was validated using actual production data from Siltec's production line. The programming of the model was verified by comparing "boundary values" with expected behavior. The model was used to predict production volumes given various absence rates and crosstraining levels. Additional experiments investigated the effects of Kanban size, equipment failure rates, operator staffing levels, and equipment capacity increases on operator staffing requirements, production throughput and WIP, and cycle time. During periods of normal operator absence (10%), productivity is improved by about 10% and cycle time is improved by about 50% if all operators are fully crosstrained. During periods of high operator absence (20%), productivity is improved by about 30% and cycle time is improved by about 50% if all operators are fully crosstrained. In all cases, equipment utilization is improved with increased crosstraining. Additional experiments allowed determination of required headcount, equipment additions, and Kanban size for optimized production throughput, WIP, and cycle time. The general conclusion of this project is an affirmation of expected behavior. Increasing crosstraining will improve productivity, especially during periods of high operator absence. Increasing Kanban size will increase throughput minimally while increasing WIP and cycle time considerably. Moderate increases in capacity at bottlenecks will result in dramatic increases in throughput. The model has been and will continue to be used to make qualitative and quantitative decisions concerning headcount, resource allocation, and expansion plans.
制造建模与优化
本项目的目的是模拟和优化Siltec的外延制造过程中的人员和设备利用。以前通过静态模型(线性规划和电子表格)对过程行为建模的尝试并没有试图解释过程线中所经历的任何可变性。利用SIMAN建立了一个简单的模型来研究交叉交叉对生产率和周期时间的影响。该模型使用Siltec生产线的实际生产数据进行了验证。通过将“边界值”与期望行为进行比较,验证了模型的规划。该模型用于预测不同缺勤率和交叉水平下的产量。其他实验调查了看板大小、设备故障率、操作人员配备水平和设备容量增加对操作人员配备需求、生产吞吐量和在制品数量以及周期时间的影响。在正常操作人员缺勤期间(10%),如果所有操作人员都完全交叉训练,则生产率提高约10%,周期时间提高约50%。如果所有作业人员都完全交叉训练,在作业人员高缺勤(20%)期间,生产率提高约30%,周期时间缩短约50%。在所有情况下,设备利用率随着交叉干扰的增加而提高。额外的实验可以确定所需的人员数量、设备添加量和看板尺寸,以优化生产吞吐量、在制品和周期时间。这个项目的总体结论是对预期行为的肯定。增加交叉将提高生产率,特别是在操作员高缺勤期间。增加看板的大小只会在很大程度上增加在制品和周期时间,而不会增加吞吐量。瓶颈处容量的适度增加将导致吞吐量的显著增加。该模型已经并将继续用于有关人员编制、资源分配和扩展计划的定性和定量决策。
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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