摘要
针对航发叶片电加工生产线受到多种随机因素影响、不能准确预知工件加工时长、需要频繁修整更换电极等特点,开展了带搬运时间柔性流水线多序列有限缓冲区排产优化问题的研究。采用了一种改进的遗传算法,加快了收敛速度;规划了航发叶片电加工生产线重排产方案,用以应对多种随机因素的影响,如机器故障、插单、撤单、加工延时等;提出了一种模型简化方法,将随机问题转化成了确定性问题。经过仿真测试,改进的遗传算法可以有效解决带搬运时间和多序列有限缓冲区的排产优化问题,且效率提高了36.9%,模型简化和重排产方法则可以有效应对生产中的异常情况,以及修整更换电极等电加工特殊工艺需求。
Aimed at the characteristics of the aero engine blade electric machining production line,such as being affected by many random factors,being unable to accurately predict the processing time of the workpiece,and requiring frequent repair and replacementof the electrode,this research addresses the scheduling optimization problem of multi sequence limited buffer zone of flexible assembly line with handling time.An improved genetic algorithm is used to accelerate the convergence speed.The rescheduling plan for the electric machining production line of aeronautical engine blades is planned to deal with the impact of various random factors,such as machine failure,order insertion,order cancellation,processing delay,etc.A model simplification method is proposed to transform the stochastic problem into the deterministic problem.The simulation test shows that the improved genetic algorithm can effectively solve the scheduling optimization problem with handling time and multiple sequence limited buffer zones,and the efficiency is increased by 36.9%.The model simplification and rescheduling methods can effectively deal with the abnormal conditions in production,as well as the special processing requirements such as repairing and changing the electrodes.
作者
蒋毅
王少航
赵晓梦
俞建峰
化春键
JIANG Yi;WANG Shaohang;ZHAO Xiaomeng;YU Jianfeng;HUA Chunjian(Jiangsu Provincial Key Laboratory of Advanced Food Manufacturing Equipment Technology,School of Mechanical Engineering,Jiangnan University,Wuxi Jiangsu 214122,China)
出处
《机械设计与研究》
CSCD
北大核心
2023年第4期135-140,共6页
Machine Design And Research
基金
国家自然科学基金资助项目(51675233)。
