【摘要】：隨著生活水平的日益提高,人們的用車理念已從“買輛車”轉(zhuǎn)變?yōu)椤百I什么車”。在這個信息發(fā)展的時代,誰更能滿足客戶的需求,誰就將占據(jù)市場的主動。由于產(chǎn)品的需求變動加快,產(chǎn)品的更新速度也同步加快,企業(yè)必須從用戶和市場的需求出發(fā)來組織生產(chǎn)。如何在市場需求變化、設(shè)備故障、物流缺料等突發(fā)情況下保持混線生產(chǎn)的穩(wěn)定,將是所有汽車企業(yè)具備市場競爭力的關(guān)鍵。本文對突發(fā)情況下混線生產(chǎn)問題進行了詳細描述,將如何從突發(fā)事件影響后的生產(chǎn)狀態(tài)恢復(fù)到原來的平穩(wěn)生產(chǎn)狀態(tài)作為研究的主要對象。在此基礎(chǔ)上,本文提出了一種基于遺傳算法和通過累計無車時間進行作息調(diào)整和生產(chǎn)序列優(yōu)化的混線生產(chǎn)控制算法。通過各車間在前后道不正常情況下不進行優(yōu)化、常規(guī)手工算法和本文算法三種算法的比較,得出常規(guī)手工算法僅適用于前道車間不正常情況;而本文算法對前后道車間不正常情況均具有良好的調(diào)控能力,尤其是在處理后道車間突發(fā)情況時效果更為明顯。通過車身至油漆儲存線實例驗證,本文算法可將最初的累計無車小時數(shù)下降到零,排產(chǎn)JPH從最初的平均28.6JPH提升至滿產(chǎn)情況的30JPH,在制品周轉(zhuǎn)量從最初的過低或過高情況改善到50%的占比水平,車型配比可從原先的“二八”配比改善到“四六”配比,驗證了本文算法的適用性。
[Abstract]:With the improvement of living standard, people's concept of car has changed from "buy a car" to "what to buy". In this era of information development, who can better meet the needs of customers, who will occupy the market initiative. Due to the rapid change of product demand and the speed of product renewal, enterprises must organize production according to the needs of users and markets. How to maintain the stability of the mixed line production under the sudden situation of market demand change, equipment failure, material shortage and so on, will be the key for all automobile enterprises to have market competitiveness. In this paper, the problem of mixing line production is described in detail, and the main research object is how to restore the production state after the sudden events to the original stable production state. On this basis, this paper presents a hybrid line production control algorithm based on genetic algorithm and the optimization of production sequence through cumulative no-car time adjustment. By comparing the conventional manual algorithm with the three algorithms in this paper, it is concluded that the conventional manual algorithm is only suitable for the abnormal situation of the former workshop. The algorithm has a good ability to control the abnormal situation of the front and rear workshop, especially when dealing with the emergency situation of the back channel workshop. Through the example of car body to paint storage line, the algorithm of this paper can reduce the initial accumulative number of hours without car to zero. Row production JPH increased from the initial average 28.6JPH to 30 JPHs of the full production situation, the turnover of in-process products improved from the initial low or too high situation to 50%, and the model ratio could be improved from the original "28" ratio to the "four or six" ratio. The applicability of this algorithm is verified.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F426.471;F273

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本文編號：2241398