基于偏差预测的装配调度与设备维护联合优化  

Joint optimization of assembly scheduling and equipment maintenance based on assembly deviation prediction

作　　者：陆志强[1] 钱岳 LU Zhiqiang;QIAN Yue(School of Mechanical and Energy Engineering,Tongji University,Shanghai 201804,China)

机构地区：[1]同济大学机械与能源工程学院,上海201804

出　　处：《计算机集成制造系统》2023年第3期811-823,共13页Computer Integrated Manufacturing Systems

基　　金：国家自然科学基金资助项目(61473211)。

摘　　要：针对飞机装配过程中因设备衰退而出现质量缺陷导致项目进度延迟并产生额外成本的问题,建立了飞机装配调度与设备预防性维护联合优化的前摄式反应调度模型,设计了带周期性检查的视情维护策略,并提出基于支持向量回归(SVR)的质量偏差预测模型和改进个体进化灰狼算法(IGWO),用以生成前摄式反应调度计划。不同维护策略对比实验表明:周期性视情维护策略相较于对比策略能够获得更低的综合成本;不同算法的对比实验对算法性能进行比较分析,验证了IGWO求解该问题的有效性。To solve the problem of project schedule delay and additional cost caused by quality defects due to equipment degradation in aircraft assembly process,a proactive response scheduling model for joint optimization of aircraft assembly scheduling and equipment preventive maintenance was established,and a condition based maintenance strategy with periodic inspection was designed.A quality deviation prediction model based on Support Vector Regression(SVR)and an Improved individual evolutionary Gray Wolf Algorithm(IGWO)were proposed to generate a proactive response scheduling plan.The comparative experiments of different maintenance strategies showed that the periodic condition based maintenance strategycould obtain lower comprehensive cost than the comparative strateg.The comparative experiments of different algorithms compared and analyzed the performance of the proposed algorithm,and the effectiveness of IGWO in solving problems was verified.

关 键 词：飞机装配 装配调度 设备预防性维护 前摄式反应调度 质量偏差预测 支持向量回归 灰狼算法 

分 类 号：V262.4[航空宇航科学与技术—航空宇航制造工程]