Reliability and Risk Evaluation Model for Intelligent Manufacturing Systems

doi:10.11908/j.issn.0253-374x.22438

Home > Archive>Volume 52, Issue 2, 2024 >313-322. DOI:10.11908/j.issn.0253-374x.22438

Reliability and Risk Evaluation Model for Intelligent Manufacturing Systems
DOI:
                        10.11908/j.issn.0253-374x.22438
                    
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                        DUAN Chun yanDUAN Chun yan
School of Mechanical Engineering， Tongji University， Shanghai 201804， China
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WANG Jia jieWANG Jia jie
School of Mechanical Engineering， Tongji University， Shanghai 201804， China
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WANG Hao boWANG Hao bo
School of Mechanical Engineering， Tongji University， Shanghai 201804， China
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ZHANG Wen juanZHANG Wen juan
School of Mechanical Engineering， Tongji University， Shanghai 201804， China
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Affiliation:School of Mechanical Engineering， Tongji University， Shanghai 201804， China
Clc Number:F27
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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.

Key words:intelligent manufacturing systems;failure modes and effects analysis;fuzzy vlsekriterijumska optimizacija i kompromisno resenje;reliability;risk evaluation;partition around medoids (PAM) clustering algorithm

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DUAN Chun yan, WANG Jia jie, WANG Hao bo, ZHANG Wen juan. Reliability and Risk Evaluation Model for Intelligent Manufacturing Systems[J].同济大学学报(自然科学版),2024,52(2):313~322

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Received:October 17,2022
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Online: February 27,2024
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