面向航空发动机装配线的知识化制造自适应优化调度  

Adaptive Optimization Scheduling of Knowledgeable Manufacture Oriented to Aircraft Engine Assembly Lines

作　　者：汪浩祥[1,2] 严洪森[1,3] 汪峥[1,3] 

机构地区：[1]东南大学,南京210096 [2]南京农业大学,南京210031 [3]东南大学复杂工程系统测量与控制教育部重点实验室,南京210096

出　　处：《中国机械工程》2014年第23期3180-3187,3194,共9页China Mechanical Engineering

基　　金：国家自然科学基金资助重点项目(60934008);国家自然科学基金资助项目(71401076;71101072);东南大学优秀博士论文基金资助项目(YBJJ1215)

摘　　要：为了解决不确定生产环境下的航空发动机装配调度问题,设计了一种面向航空发动机装配线的知识化制造自适应优化调度算法。算法采用强化学习和过程仿真相结合的调度策略求解方式,以最小化提前期惩罚费用和完工时间成本为调度目标,给出了航空发动机装配的Q学习自适应调度模型;针对装配调度问题定义了四个新的调度规则,定义了航空发动机装配的四个状态特征用于对系统状态进行描述,并针对调度目标设计了合理的回报函数。仿真实验结果表明,在调度过程中,采用提出的Q学习方法在多数情况下都远优于其他规则,尤其在装配任务到达频繁的情况下,总体上表现出更好的优势,显示了良好的自适应性能。To solve the problem of aircraft engine assembly scheduling in an uncertain production environment,an adaptive optimization scheduling algorithm of a knowledgeable manufacture oriented to an aircraft engine assembly lines was proposed,where a scheduling-policy solved mechanism combining Q learning and process simulation was used.A Q-learning adaptive scheduling model of aircraft engine assembly was built on the objective function of minimizing earliness penalty and completion time cost.Then four new scheduling rules were provided for assembly scheduling problem,four state features of aircraft engine assembly were defined for describing system states,and the proper reward function was designed for the objective function.Some simulation experiments indicate that the proposed algorithm outperforms other scheduling rules much in most cases,especially,better results are generally achieved with the frequently changes of task arrival rates to show good adaptive performance.

关 键 词：调度 航空发动机装配 知识化制造自适应 Q学习 

分 类 号：TH165[机械工程—机械制造及自动化]