eM-Plant在电容式电压互感器生产布局优化中的应用研究

发布时间：2018-02-01 15:11

本文关键词： 布局优化遗传算法 eM-Plant仿真 SLP　出处：《上海交通大学》2015年硕士论文　论文类型：学位论文

【摘要】：生产布局一直是企业规划的关键问题,如何设计出一个好的布局,既要考虑布局要使物流成本最低,还要满足企业各种约束条件,国内外在生产布局方面做了大量的研究,并取得了很多研究成果。目前,车间各工序之间的在制品没有合理规划;因车间早期规划的产能小,现在关键工序设备能力不足,需借用其他车间设备完成生产任务,物流路径迂回曲折。本文运用仿真技术,确定车间各区域的在制品设置量,然后使用遗传算法,求出物流搬运量最小的布局设计。本文的研究过程为:基于S公司的实际情况,分析各区域之间的综合相互关系;对各区域不同的班次不同的工艺之间,通过仿真软件预先设定一个较高的在制品容量,然后运行一段时间,统计各工序之间实际产生的在制品最大数量以及需要的瓶颈工序关键设备的最大数量,并根据实际情况,适当调整关键设备数量及缓存量,用仿真验证新设置的在制品数量和关键设备数量对产出没有影响。因在制品数量大,占地较多,将在制品占用面积跟设备面积结合在一起,作为区域面积;最后使用遗传算法,将综合相互关系替代原遗传算法中的物流量,将各区域面积作为遗传算法初始条件,设定适应度函数为物流路径最小,利用遗传算法全局搜索寻优能力,求解生产布局优化问题。本文把适应度函数作为评价指标,并根据实际约束条件调整区域位置,对于快速求解生产区域布局问题具有重要的意义。
[Abstract]:Production layout has always been the key problem of enterprise planning, how to design a good layout, it is necessary to consider the layout to make the lowest logistics costs, but also to meet the various constraints of the enterprise. At home and abroad, a lot of research has been done in production layout, and a lot of research results have been made. At present, there is no reasonable planning of WIP between workshop processes; Due to the small capacity of early planning of workshop and the insufficient capacity of critical process equipment, other workshop equipment should be used to complete the production task, and the logistics path is tortuous. This paper uses simulation technology. Determine the amount of in-process set in each area of the workshop, and then use genetic algorithm to find out the layout design with the minimum logistics handling. The research process of this paper is: based on the actual situation of S company. Analysis of integrated interrelationships among regions; For different processes in different shifts in different regions, a higher WIP capacity is pre-set by simulation software, and then run for a period of time. Statistics the actual production of the maximum number of in-process products and the maximum number of bottleneck process key equipment, and according to the actual situation, adjust the number of key equipment and cache. It is verified by simulation that the quantity of WIP and the number of key equipment have no effect on the output. Because of the large quantity of WIP and the large area of WIP, the occupied area of WIP is combined with the area of equipment as the area of area. Finally, the genetic algorithm is used to replace the logistics flow in the genetic algorithm by comprehensive interrelation. The area of each region is taken as the initial condition of the genetic algorithm, and the fitness function is set as the minimum logistics path. In this paper, the fitness function is used as the evaluation index, and the region position is adjusted according to the actual constraints by using the global searching ability of genetic algorithm to solve the production layout optimization problem. It is of great significance to solve the problem of production area layout quickly.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM451

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