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首页 > 过刊浏览>2024年第52卷第2期 >313-322. DOI:10.11908/j.issn.0253-374x.22438
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智能制造系统可靠性与风险评估模型
作者:
作者单位:

同济大学 机械与能源工程学院，上海 201804

作者简介:

段春艳，副教授，管理学博士，主要研究方向为智能制造与风险管理等。 E-mail： duanchunyan77@163.com

通讯作者:

张文娟，副研究员，管理学博士，主要研究方向为智能服务工程等。E-mail： 08143@tongji.edu.cn

中图分类号:

F27

基金项目:

国家自然科学基金资助项目（72171170）；中央高校基本科研业务费专项资金资助（22120210535）；上海市浦江人才计划资助（20PJ1413700）。


Reliability and Risk Evaluation Model for Intelligent Manufacturing Systems
Author:
Affiliation:

School of Mechanical Engineering， Tongji University， Shanghai 201804， China

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    摘要:

    针对智能制造系统的可靠性与风险评估问题，提出一种基于改进失效模式与影响分析（FMEA）的智能制造系统可靠性与风险评估模型。从创新运用组合权重、逼近理想解排序法思想和模糊多准则妥协解排序法的角度对传统FMEA模型进行改进；基于逼近理想解排序法思想得到专家权重，减少了专家团队对失效模式风险因子分析过程中的个体差异；使用模糊层次分析法和熵权法分别计算风险因子的主观和客观权重，减少了风险因子确定的主观性。最后，运用围绕中心点划分（PAM）聚类算法对改进模型得到的结果进行分析，并应用于智能制造系统风险评估中，确定了智能制造系统中各失效模式的重要程度，通过比较分析验证了改进模型的有效性。

    Abstract:

    To address the problem of reliability and risk assessment of intelligent manufacturing systems， an improved failure mode and effects analysis （FMEA） model for intelligent manufacturing systems is proposed for the reliability and risk evaluation of intelligent manufacturing systems. The FMEA model is improved from the perspective of innovative use of combined weight， the idea of technique for order preference by similarity to ideal solution and fuzzy vlsekriterijumska optimizacija i kompromisno resenje. In the calculation of the weights of decision makers， the weights of decision makers are obtained based on the idea of technique for order preference by similarity to ideal solution， in which the fuzzy analytic hierarchy process is used to calculate the subjective weight of risk factors and the entropy weight method is used to calculate the objective weight of the risk factors， which reduces the subjectivity. The results obtained from the improved model are analyzed by applying partition around medoids （PAM） clustering algorithm and applied to the risk evaluation of intelligent manufacturing systems， The importance of each failure mode in the intelligent manufacturing systems is determined， and the effectiveness of the improved model is verified by comparative analysis.

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段春艳,王佳洁,王皓博,张文娟.智能制造系统可靠性与风险评估模型[J].同济大学学报(自然科学版),2024,52(2):313~322

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  • 收稿日期:2022-10-17
  • 在线发布日期: 2024-02-27
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