本文選題：裝配線平衡 + Witness��； 參考：《浙江理工大學(xué)》2017年碩士論文

【摘要】：自從裝配線被研究以來,它已經(jīng)進(jìn)入到了各行各業(yè),得到了充分的發(fā)展。近幾年由于多種少量的生產(chǎn)方式的不斷發(fā)展,混流裝配線的概念逐漸被人們所熟知。通過平衡混流裝配線,以及對產(chǎn)品的生產(chǎn)進(jìn)行排序優(yōu)化,可以加快產(chǎn)品流動,減少生產(chǎn)周期,消除工程瓶頸,并在其基礎(chǔ)上實現(xiàn)單元生產(chǎn),提高生產(chǎn)應(yīng)變能力,對應(yīng)市場變化從而實現(xiàn)柔性生產(chǎn)系統(tǒng)�，F(xiàn)在一般有三種方法研究混流裝配線平衡,他們分別是數(shù)學(xué)規(guī)劃法、編程算法和傳統(tǒng)的IE理論方法。前二者的研究者眾多,也都取得了較好的研究成果,但是近年來的發(fā)展遇到了瓶頸,學(xué)術(shù)理論和實際的生產(chǎn)運營越來越脫節(jié),傳統(tǒng)的IE方法比較簡單,但卻造就了它的較廣范圍的適用性,而且對于問題的解決具有較強的實用性。本文綜合利用了基礎(chǔ)IE方法和改進(jìn)的粒子群算法,首先對M叉車廠的內(nèi)燃車總裝線進(jìn)行了平衡分析,利用仿真軟件Witness驗證,對比改善前后的平均在制庫存和總體工時利用率;接著以最小化超載作業(yè)時間和物料消耗平準(zhǔn)化作為優(yōu)化目標(biāo)進(jìn)行建模,并分別分配權(quán)重,從而得到雙目標(biāo)優(yōu)化模型,利用改進(jìn)的粒子群算法得出該模型的近似最優(yōu)解,得到該混流裝配線的最優(yōu)投產(chǎn)順序。本文的主要內(nèi)容為五部分。首先,緒論部分闡述了裝配線平衡研究的國內(nèi)外現(xiàn)狀及趨勢,對裝配線平衡的基本形式和方法,研究原則和目的進(jìn)行了分析,對不同研究方法進(jìn)行簡單的比較,并給出了課題的體系結(jié)構(gòu);然后,理論綜述部分介紹了基礎(chǔ)IE的相關(guān)理論,比如ECRS四大原則、方法研究、作業(yè)測定、5W1H六合分析法等,說明了研究裝配線平衡的相關(guān)術(shù)語、公式和評價指標(biāo),并對粒子群算法的基本原理和基本流程進(jìn)行了說明,最后指出將運用改進(jìn)的粒子群算法對混流裝配線的投產(chǎn)排序問題進(jìn)行求解;其次,以某大型企業(yè)M叉車廠FD30車型裝配線為研究對象,通過現(xiàn)場對作業(yè)人員的作業(yè)進(jìn)行詳細(xì)的調(diào)查研究,進(jìn)而找到各工位的生產(chǎn)時間,并利用這些數(shù)據(jù)確定裝配線的瓶頸工序,接著通過理論與實際相結(jié)合的方式對給車型總裝線進(jìn)行平衡分析并改善,提高了生產(chǎn)效率,并推廣到其他車型上去,得到相似的良好結(jié)果;再者,用離散仿真軟件Witness對改善前后的裝配線生產(chǎn)狀況進(jìn)行分析,得到改善后的平均在制品庫存以及平均總裝配時間總體比改善前的要好,從而具體驗證了該叉車裝配線平衡后的效果;最后,針對M叉車廠的混流裝配線排序問題進(jìn)行了描述,選擇以最小化超載作業(yè)時間和物料消耗平準(zhǔn)化作為優(yōu)化目標(biāo)進(jìn)行建模,并分別對其分配權(quán)重,從而得到雙目標(biāo)優(yōu)化模型。利用改進(jìn)的粒子群算法得出該模型的最優(yōu)解,從而得到該叉車混流裝配線的最優(yōu)投產(chǎn)順序。
[Abstract]:Since the assembly line has been studied, it has entered all walks of life and been fully developed. In recent years, the concept of mixed-flow assembly line has been well known due to the continuous development of a variety of production methods. By balancing the mixed flow assembly line and optimizing the production of products, the flow of products can be accelerated, the production cycle can be reduced, the bottleneck of engineering can be eliminated, and the unit production can be realized on the basis of which the capacity of production strain can be improved. Corresponding to market changes to achieve flexible production system. At present, there are three methods to study the balance of mixed-flow assembly line. They are mathematical programming, programming algorithm and traditional IE theory. The former two researchers are numerous and have made good research results, but in recent years the development has encountered a bottleneck, academic theory and practical production and operation are more and more disjointed, the traditional IE method is relatively simple. But it creates a wide range of applicability, and has a strong practicality for the solution of the problem. In this paper, the basic IE method and the improved particle swarm optimization algorithm are synthetically used. Firstly, the balance analysis of the assembly line of the internal combustion car in the M forklift plant is carried out. The simulation software Witness is used to verify and compare the average in-control inventory and the total man-hour utilization ratio before and after the improvement. Then, the optimization objective is to minimize overloading operation time and material consumption, and the weight is assigned to get the two-objective optimization model. The improved particle swarm optimization algorithm is used to obtain the approximate optimal solution of the model. The optimal production sequence of the mixed flow assembly line is obtained. The main content of this paper is five parts. First of all, the introduction part describes the current situation and trend of assembly line balance research, analyzes the basic forms and methods of assembly line balance, the research principles and purposes, and makes a simple comparison of different research methods. Then, the related theories of basic IE are introduced, such as the four principles of ECRS, the research of methods, the method of work determination and the analysis of 5W1H, and the related terms of studying the balance of assembly line are explained. The formula and evaluation index, and the basic principle and flow of particle swarm optimization algorithm are explained. Finally, it is pointed out that the hybrid assembly line scheduling problem will be solved by the improved particle swarm optimization algorithm. Secondly, Taking FD30 type assembly line of M forklift truck factory in a large enterprise as the research object, through the detailed investigation and study of the operators' work on the spot, the production time of each station is found, and the bottleneck process of the assembly line is determined by using these data. Then through the combination of theory and practice to analyze and improve the balance of the vehicle assembly line, improve the production efficiency, and spread to other models to get similar good results; The production condition of assembly line before and after improvement is analyzed by using the discrete simulation software Witness. The average in-process inventory and the average total assembly time of the improved assembly line are generally better than those before the improvement. Finally, the scheduling problem of mixed flow assembly line in M forklift plant is described, and the optimization goal is to minimize overloading operation time and material consumption. The two objective optimization model is obtained by assigning the weight to it. The optimal solution of the model is obtained by using the improved particle swarm optimization (PSO) algorithm, and the optimal production sequence of the mixed flow assembly line of the forklift truck is obtained.
【學(xué)位授予單位】：浙江理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TH186

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