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

被引：0
|
作者：
Lu Z. [1 ]
Qian Y. [1 ]
机构：
[1] School of Mechanical and Energy Engineering, Tongji University, Shanghai
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2023年 / 29卷 / 03期
关键词：
aircraft assembly; assembly scheduling; equipment preventive maintenance; gray wolf algorithm; proactive response scheduling; quality deviation prediction; support vector regression;
D O I：
10.13196/j.cims.2023.03.011
中图分类号：
学科分类号：
摘要：
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. © 2023 CIMS. All rights reserved.
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页码：811 / 823
页数：12
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