【摘要】：生產(chǎn)線平衡是制造企業(yè)底層生產(chǎn)流程設(shè)計規(guī)劃和重組優(yōu)化的重要方法之一，即在給定的約束條件下，將一系列具有優(yōu)先關(guān)系的作業(yè)要素分配給合適數(shù)量的工作站，以實現(xiàn)生產(chǎn)線的平衡。生產(chǎn)線的不平衡會造成大量的工時損失，也會造成大量的在制品堆積，嚴(yán)重時會導(dǎo)致生產(chǎn)的中止。 本文在總結(jié)和分析了近年來國內(nèi)外研究生產(chǎn)線平衡技術(shù)方法的基礎(chǔ)上，針對現(xiàn)有生產(chǎn)平衡技術(shù)中研究較少的方面-第二類生產(chǎn)線平衡問題，將工業(yè)工程方法與改進遺傳算法相結(jié)合，提出一種用改進遺傳算法來分析、解決生產(chǎn)線平衡問題的方法技術(shù)，并把這種方法應(yīng)用到實際生產(chǎn)線平衡問題的改善上，取得了較好的效果。 本文首先對生產(chǎn)線平衡問題概念進行了基本闡述，并回顧總結(jié)了國內(nèi)外生產(chǎn)線平衡問題的常用求解思路和算法。在此基礎(chǔ)上針對本公司Blue Line2產(chǎn)品生產(chǎn)線現(xiàn)狀進行了分析，提出了該生產(chǎn)線平衡問題為第二類生產(chǎn)線平衡問題，圍繞該生產(chǎn)線平衡優(yōu)化目標(biāo)，使用傳統(tǒng)工業(yè)工程方法對生產(chǎn)線平衡問題進行了初步的研究，使生產(chǎn)線的平衡率提高到71%左右，同時考慮到該生產(chǎn)線工序多達近40個，傳統(tǒng)工業(yè)工程方法不能進一步給出優(yōu)化改善的情況下，提出了利用改進遺傳算法來研究上述問題。本文利用Matlab編程工具完成了改進遺傳算法的編程，，并利用經(jīng)典生產(chǎn)平衡問題對算法進行了驗證，利用該算法對實際生產(chǎn)線進行了模擬優(yōu)化，結(jié)果表明，此種算法能夠較好的解決第二類生產(chǎn)平衡問題，對提高生產(chǎn)線平衡率和降低生產(chǎn)線的負(fù)荷不平衡有較好的結(jié)果。 最后在基于Matlab的改進遺傳算法優(yōu)化后的結(jié)果下對實際裝配生產(chǎn)線平衡問題進行優(yōu)化平衡，并對平衡優(yōu)化前后的指標(biāo)進行了對比和評價。 本文通過對第二類生產(chǎn)平衡問題的深入研究，并采用改進遺傳算法對問題進行了優(yōu)化求解，該研究結(jié)果表明該研究在解決平衡生產(chǎn)線，企業(yè)資源優(yōu)化配置，提高企業(yè)生產(chǎn)效率，提高企業(yè)競爭力具有較好效果。
[Abstract]:Production line balance is one of the most important methods to design and reorganize manufacturing processes in manufacturing enterprises. Under given constraints, a series of operational elements with priority relationship are assigned to a suitable number of workstations. In order to achieve the balance of the production line. The imbalance of the production line will cause a lot of man-hour loss, also will cause a large number of in-process product accumulation, serious will lead to the suspension of production. On the basis of summarizing and analyzing the research methods of production line balance technology at home and abroad in recent years, this paper aims at the problem of the second kind of production line balance, which is less studied in the existing production balance technology. Combining the industrial engineering method with the improved genetic algorithm, this paper puts forward a method and technology of analyzing and solving the problem of production line balance by using the improved genetic algorithm, and applies this method to the improvement of the balance problem of the actual production line. Good results have been obtained. In this paper, the concept of production line balance problem is introduced, and the common solutions and algorithms of production line balance problem at home and abroad are reviewed and summarized. Based on the analysis of the current situation of the Blue Line2 product line of our company, the paper puts forward that the balance problem of the production line is the second kind of production line balance problem, and focuses on the optimization goal of the product line balance. The balance problem of production line is studied by using traditional industrial engineering method, and the balance rate of production line is raised to about 71%. Considering that there are as many as 40 processes in the production line, the balance rate of the production line is increased to about 71%. Under the condition that the traditional industrial engineering method can not give the optimization improvement further, the improved genetic algorithm is proposed to study the above problems. In this paper, Matlab programming tool is used to complete the programming of improved genetic algorithm, and the algorithm is verified by classical production balance problem. The algorithm is used to simulate and optimize the actual production line, and the results show that: This algorithm can solve the problem of the second kind of production balance better, and has a good result to improve the balance rate of the production line and reduce the unbalanced load of the production line. Finally, under the optimized results of the improved genetic algorithm based on Matlab, the balance problem of the actual assembly production line is optimized, and the indexes before and after the optimization are compared and evaluated. In this paper, the second kind of production balance problem is studied deeply, and the improved genetic algorithm is used to solve the problem. The results show that this research can solve the problem of balancing production line, optimizing the allocation of enterprise resources and improving the production efficiency of enterprises. Improving the competitiveness of enterprises has a good effect.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP18;F416.6

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