本文選題：復(fù)雜　切入點：混流生產(chǎn)線車間系統(tǒng)　出處：《五邑大學(xué)》2012年碩士論文

【摘要】：從20世紀(jì)70年代開始,隨著市場開始從賣方市場向買方市場開始轉(zhuǎn)變,大批量、單品種的生產(chǎn)方式也開始變向多品種、小批量的生產(chǎn)方式轉(zhuǎn)化。我國是一個制造業(yè)大國,混流生產(chǎn)線車間在我國制造業(yè)車間比較具有代表性。混流生產(chǎn)線車間系統(tǒng)的規(guī)劃問題是一個企業(yè)重要的開局部分,對一個復(fù)雜混流生產(chǎn)線車問系統(tǒng)的規(guī)劃研究有著十分實際的意義。 本文主要是探討一種解決混流生產(chǎn)線車間系統(tǒng)的規(guī)劃問題的方法。 首先,運用復(fù)雜系統(tǒng)的理論對混流生產(chǎn)線車間系統(tǒng)進(jìn)行分析,可以知道混流生產(chǎn)線車間系統(tǒng)具有結(jié)構(gòu)復(fù)雜性、組成單元復(fù)雜性、交互環(huán)節(jié)復(fù)雜性和行為復(fù)雜性。混流生產(chǎn)線車間系統(tǒng)具有復(fù)雜適應(yīng)系統(tǒng)的聚集、非線性、流、多樣性四大特征和標(biāo)識、內(nèi)部模型、積木塊三大機(jī)制,而混流生產(chǎn)線車間系統(tǒng)是一個不斷與外界進(jìn)行能量交換的開放系統(tǒng),是一個復(fù)雜適應(yīng)系統(tǒng)。對于復(fù)雜適應(yīng)系統(tǒng)的理論和研究方法我們都可以對混流生產(chǎn)線車間系統(tǒng)規(guī)劃問題進(jìn)行應(yīng)用。 其次,引入遺傳算法對傳統(tǒng)的系統(tǒng)布局規(guī)劃方法(SLP)進(jìn)行流程改進(jìn)。由原來設(shè)備具體面積關(guān)系修改為設(shè)定一個約束范圍,運用物流關(guān)系來代替。這樣就避免了原來SLP方案中繪制作業(yè)單位位置相關(guān)圖和面積相關(guān)圖時需不斷的手工調(diào)整和修正這一流程,使得SLP更加快捷有效；同時還降低了由人的主觀因素帶來的影響。 再次,在遺傳算法應(yīng)用到SLP流程中,通過增加一層編碼層(工藝—單元)來進(jìn)行約束,使得設(shè)備、單元、工藝三者集成考慮,系統(tǒng)性更加合理,運算更加快捷。 最后,通過基于遺傳算法和SLP相結(jié)合的規(guī)劃方法進(jìn)行實例分析,與單獨使用遺傳算法的規(guī)劃方法進(jìn)行結(jié)果比較,可以看出不僅改善了流程、減少了運行時間而且規(guī)劃目標(biāo)更加接近公司要求；與單獨使用傳統(tǒng)的SLP方法(公司原來用的方案)進(jìn)行結(jié)果比較,可以看出物流成本降低50%左右,在過程中避免了原來SLP方案中繪制作業(yè)單位位置相關(guān)圖和面積相關(guān)圖時需不斷的手工調(diào)整和修正這一流程,有效降低了人的主觀因素帶來的影響,非常符合公司日標(biāo)規(guī)劃需求。 相關(guān)數(shù)值實驗表明本文提出的解決混流生產(chǎn)線車問系統(tǒng)的規(guī)劃問題的方法—基于遺傳算法和SLP相結(jié)合的方法能夠更加有效地使全局物流費用得以降低,提高了設(shè)計質(zhì)量,簡化了設(shè)計步驟,取得了滿意的效果。具有一定的實際應(yīng)用價值和推廣意義。
[Abstract]:Since 1970s, as the market began to change from the seller's market to the buyer's market, the mode of production of large quantity and single variety began to change to multi-variety and small-batch mode of production.China is a large manufacturing country, the mixed production line workshop in our manufacturing workshop is more representative.The planning of hybrid production line workshop system is an important starting part of an enterprise, which has a very practical significance for the planning research of a complex mixed production line vehicle system.This paper mainly discusses a method to solve the planning problem of mixed flow production line workshop system.Firstly, the theory of complex system is used to analyze the hybrid production line workshop system. It can be known that the hybrid production line workshop system has structural complexity, component unit complexity, interaction complexity and behavior complexity.The workshop system of mixed-flow production line has four characteristics of complex adaptive system, such as aggregation, nonlinearity, flow and diversity, internal model and building block.The hybrid production line workshop system is an open system for energy exchange with the outside world and is a complex adaptive system.For the theory and research method of complex adaptive system, we can apply to the problem of workshop system planning of mixed flow production line.Secondly, genetic algorithm is introduced to improve the traditional system layout planning method (SLP).Change from original equipment specific area relation to set a restriction range, use logistics relation to replace.This avoids the need for manual adjustment and correction of the original SLP scheme when drawing the job unit position correlation and area correlation maps, which makes the SLP more efficient and efficient, and reduces the influence of human subjective factors.Thirdly, when genetic algorithm is applied to SLP process, a layer of coding layer (process-unit) is added to constrain, so that the integration of equipment, unit and process is considered, and the system is more reasonable and the operation is faster.Finally, through the case analysis based on the combination of genetic algorithm and SLP, compared with the planning method using genetic algorithm alone, we can see that not only improved the process,The running time is reduced and the planning goal is closer to the requirements of the company. Compared with the results of the traditional SLP method used by the company alone, we can see that the logistics cost is reduced by about 50%.In the process, it avoids the need of manual adjustment and correction of the original SLP scheme to draw the job unit position correlation map and the area correlation map, which effectively reduces the impact of human subjective factors and meets the needs of the company's daily standard planning.The related numerical experiments show that the method proposed in this paper, which is based on genetic algorithm and SLP, can effectively reduce the global logistics cost and improve the design quality.The design steps are simplified and satisfactory results are obtained.It has certain practical application value and popularization significance.
【學(xué)位授予單位】：五邑大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：TH181

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