考虑时间不确定的再制造工艺方案决策方法  

Decision-making methods for remanufacturing process programs considering time uncertainty

作　　者：王蕾[1] 刘政 郭钰瑶 张泽琳 夏绪辉 WANG Lei;LIU Zheng;GUO Yuyao;ZHANG Zelin;XIA Xuhui(Key Laboratory of Metallurgical Equipment and Control Technology,Wuhan University of Science&Technology,Wuhan 430081,China;Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering,Wuhan University of Science&Technology,Wuhan 430081,China)

机构地区：[1]武汉科技大学冶金装备及其控制教育部重点实验室,武汉430081 [2]武汉科技大学机械传动与制造工程湖北省重点实验室,武汉430081

出　　处：《现代制造工程》2024年第10期113-122,共10页Modern Manufacturing Engineering

基　　金：国家自然科学基金资助项目(52275503);湖北省杰出青年基金项目(2023AFA092)。

摘　　要：针对退役零件失效状态复杂及设备能力各异,导致再制造工艺方案决策困难的问题,提出一种考虑时间不确定的再制造工艺方案决策方法。分析退役零件再制造工艺过程及其时间的不确定性,提出考虑失效状态的再制造工艺时间改进模糊神经网络预测方法;构建以时间、成本和能耗为优化目标的再制造工艺方案决策模型,采用遗传-粒子群优化算法快速求解;以退役轧辊再制造工艺方案决策过程为例,验证该方法的有效性和实用性。Aiming at the problems that the complex failure state of retir parts and the different capabilities of equipments make it difficult to make decisions on remanufacturing process programs,a decision-making method for remanufacturing process programs considering time uncertainty was proposed.Analyzing the uncertainty of the remanufacturing process of retired parts and its time,a fuzzy neural network prediction method was proposed to improve the time of remanufacturing process considering the failure state;a decision-making model of remanufacturing process program was constructed with the optimization objectives of time,cost and energy consumption,and a genetic-particle swarm optimization algorithm was adopted for rapid solution;the effectiveness and practicability of the method were verified by taking the decision-making process of remanufacturing process program of retired rolls as an example.

关 键 词：再制造 时间不确定 工艺时间预测 改进模糊神经网络 决策 

分 类 号：TH17[机械工程—机械制造及自动化]