基于Petri网及遗传算法的混流装配线重构

混流装配线在当今制造业中极大地提高了企业响应市场的能力,然而混流装配线上经常出现有的装配工位非常繁忙,有的装配工位处于闲置状态的情状,分析可知,这一现象由多品种混流生产造成,将直接导致生产劳动力的浪费和设备开动率的降低。为解决这一问题,在Petri网建模的基础上,提出了一种基于工作站的装配线重构,并在此基础上采用遗传算法进行排序,以达到较小成本及较短时间内的装配线重构。该方法在订单无规律的大幅度波动下十分有效,既有效分配了资源,又大大缩短了响应市场的时间。

Reconstruction of Mixed Model Assembly Lines based on Petri Net and Genetic Algorithm

Mixed model assembly line have improved the ability of enterprises to respond to the market greatly in today＇s manufacturing industry,but there are also some problems on the assembly line,such as sometimes some assembly stations are very busy,but some assembly stations are idle.This phenomenon is due to the varieties production all in one line,which directly leads to lower production and equipment idle.This problem can be solved based on Petri net modeling,the paper proposed one reconstruction method based on workstation,and also used the genetic algorithm in order to achieve smaller costs when the time is short.This method is very effective when order changed obviously,and also can save the time greatly.