本文關(guān)鍵詞： 布局優(yōu)化 遺傳算法 eM-Plant仿真 SLP　出處：《上海交通大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：生產(chǎn)布局一直是企業(yè)規(guī)劃的關(guān)鍵問題,如何設(shè)計(jì)出一個(gè)好的布局,既要考慮布局要使物流成本最低,還要滿足企業(yè)各種約束條件,國內(nèi)外在生產(chǎn)布局方面做了大量的研究,并取得了很多研究成果。目前,車間各工序之間的在制品沒有合理規(guī)劃;因車間早期規(guī)劃的產(chǎn)能小,現(xiàn)在關(guān)鍵工序設(shè)備能力不足,需借用其他車間設(shè)備完成生產(chǎn)任務(wù),物流路徑迂回曲折。本文運(yùn)用仿真技術(shù),確定車間各區(qū)域的在制品設(shè)置量,然后使用遺傳算法,求出物流搬運(yùn)量最小的布局設(shè)計(jì)。本文的研究過程為:基于S公司的實(shí)際情況,分析各區(qū)域之間的綜合相互關(guān)系;對(duì)各區(qū)域不同的班次不同的工藝之間,通過仿真軟件預(yù)先設(shè)定一個(gè)較高的在制品容量,然后運(yùn)行一段時(shí)間,統(tǒng)計(jì)各工序之間實(shí)際產(chǎn)生的在制品最大數(shù)量以及需要的瓶頸工序關(guān)鍵設(shè)備的最大數(shù)量,并根據(jù)實(shí)際情況,適當(dāng)調(diào)整關(guān)鍵設(shè)備數(shù)量及緩存量,用仿真驗(yàn)證新設(shè)置的在制品數(shù)量和關(guān)鍵設(shè)備數(shù)量對(duì)產(chǎn)出沒有影響。因在制品數(shù)量大,占地較多,將在制品占用面積跟設(shè)備面積結(jié)合在一起,作為區(qū)域面積;最后使用遺傳算法,將綜合相互關(guān)系替代原遺傳算法中的物流量,將各區(qū)域面積作為遺傳算法初始條件,設(shè)定適應(yīng)度函數(shù)為物流路徑最小,利用遺傳算法全局搜索尋優(yōu)能力,求解生產(chǎn)布局優(yōu)化問題。本文把適應(yīng)度函數(shù)作為評(píng)價(jià)指標(biāo),并根據(jù)實(shí)際約束條件調(diào)整區(qū)域位置,對(duì)于快速求解生產(chǎn)區(qū)域布局問題具有重要的意義。
[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.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TM451

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