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Journal of Optimization in Industrial Engineering
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shaghaghi, M., Rezaie, K. (2012). Failure Mode and Effects Analysis Using Generalized Mixture Operators. Journal of Optimization in Industrial Engineering, 5(11), 1-10.
mahdi shaghaghi; Kamran Rezaie. "Failure Mode and Effects Analysis Using Generalized Mixture Operators". Journal of Optimization in Industrial Engineering, 5, 11, 2012, 1-10.
shaghaghi, M., Rezaie, K. (2012). 'Failure Mode and Effects Analysis Using Generalized Mixture Operators', Journal of Optimization in Industrial Engineering, 5(11), pp. 1-10.
shaghaghi, M., Rezaie, K. Failure Mode and Effects Analysis Using Generalized Mixture Operators. Journal of Optimization in Industrial Engineering, 2012; 5(11): 1-10.

Failure Mode and Effects Analysis Using Generalized Mixture Operators

Article 1, Volume 5, Issue 11, Summer and Autumn 2012, Page 1-10  XML PDF (845 K)
Document Type: Original Manuscript
Authors
mahdi shaghaghi 1; Kamran Rezaie2
1Department of Industrial engineering, Qazvin University, Iran
2Department of Industrial engineering, National University, Iran
Abstract
Failure mode and effects analysis (FMEA) is a method based on teamwork to identify potential failures and problems in a system, design, process and service in order to remove them. The important part of this method is determining the risk priorities of failure modes using the risk priority number (RPN). However, this traditional RPN method has several shortcomings. Therefore, in this paper we propose a FMEA
which uses generalized mixture operators to determine and aggregate the risk priorities of failure modes. In a numerical example, a FMEA of the LGS gas type circuit breaker product in Zanjan Switch Industries in Iran is presented to further illustrate the proposed method. The results show that the suggested approach is simple and provides more accurate risk assessments than the traditional RPN. 
Keywords
Failure mode and effects analysis (FMEA); Generalized mixture operators; Fuzzy set; Risk priority number
Main Subjects
Design of Experiment
Statistics
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PDF Download: 4,274
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