基于平均停歇时间的多品种混流生产线智能排序策略

Intelligent Sequencing Problem of Multi-Variety Mixed-Model Production Line Based on Mean Residence Time

摘要:

“工业4.0”智能制造模式下的多品种混流生产线各工装/夹具、工具/量具和系统用例切换频繁，极易导致生产突发异常致使工作站出现短暂停歇风险。通过分析多品种混流生产线产品多态性引起的不确定性因素，提出了平均停歇时间（MRT），研究考虑MRT的多品种混流生产线最小生产循环周期，建立了基于产品进入生产线顺序的产品作业时间表，通过引入MRT关键变量至最小循环周期优化目标，构建了智能排序数学模型，并利用Palmer原理设计了改进遗传算法，实现了多品种混流生产线智能排序问题的高效求解，最后实例验证了该方法的可行性和有效性。

Abstract:

The frequent switching of tooling/fixture， tool/gauge and system utilizationse cases in the multi-variety mixed-model production line under the mode of "industrial 4.0" intelligent manufacturing can easily lead to abnormal production and short-term stopping risk in workstations. First， the mean residence time（MRT） was proposed by analyzing the uncertainties caused by product polymorphism in the multi-variety mixed-model production line. Next， this study by considerings the minimum production cycle of the MRT multi-variety mixed-model production line， establishes the product operation schedule based on the sequence of products entering the production line， and establishes an intelligent sequencing mathematical model by introducing the key variables of MRT to the objective of minimal cycle optimization. After that， based on the Palmer principle， an improved genetic algorithm was designed to solve the intelligent sequencing problem of the multi product mixed-model production line. Finally， the feasibility and validity of this method are verified by an example.