整车厂混线生产控制研究及应用
发布时间：2018-09-13 14:11
【摘要】：随着生活水平的日益提高,人们的用车理念已从“买辆车”转变为“买什么车”。在这个信息发展的时代,谁更能满足客户的需求,谁就将占据市场的主动。由于产品的需求变动加快,产品的更新速度也同步加快,企业必须从用户和市场的需求出发来组织生产。如何在市场需求变化、设备故障、物流缺料等突发情况下保持混线生产的稳定,将是所有汽车企业具备市场竞争力的关键。本文对突发情况下混线生产问题进行了详细描述,将如何从突发事件影响后的生产状态恢复到原来的平稳生产状态作为研究的主要对象。在此基础上,本文提出了一种基于遗传算法和通过累计无车时间进行作息调整和生产序列优化的混线生产控制算法。通过各车间在前后道不正常情况下不进行优化、常规手工算法和本文算法三种算法的比较,得出常规手工算法仅适用于前道车间不正常情况;而本文算法对前后道车间不正常情况均具有良好的调控能力,尤其是在处理后道车间突发情况时效果更为明显。通过车身至油漆储存线实例验证,本文算法可将最初的累计无车小时数下降到零,排产JPH从最初的平均28.6JPH提升至满产情况的30JPH,在制品周转量从最初的过低或过高情况改善到50%的占比水平,车型配比可从原先的“二八”配比改善到“四六”配比,验证了本文算法的适用性。
[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.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.471;F273
本文编号：2241398
[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.
【学位授予单位】：上海交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.471;F273
【参考文献】
相关期刊论文 前2条
1 王海燕;陈晶;;模拟退火算法在混流装配投产中的应用[J];制造业自动化;2012年11期
2 陈宏,何小荣,陈丙珍,邱彤;基于遗传算法的炼油厂多周期生产库存管理优化[J];清华大学学报(自然科学版);2004年03期
，本文编号：2241398
本文链接：https://www.wllwen.com/jingjilunwen/gongyejingjilunwen/2241398.html
