Volume 29, Issue 3 (IJIEPR 2018)                   IJIEPR 2018, 29(3): 359-376 | Back to browse issues page


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Vaysi A, Rohani A, Tabasizadeh M, khodabakhshian R, Kolahan F. Using Fuzzy FMEA approach to improve decision-making process in CNC machine Electrical and control equipment failure prediction. IJIEPR. 2018; 29 (3) :359-376
URL: http://ijiepr.iust.ac.ir/article-1-835-en.html
1- Department of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran.
2- Department of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran. , arohani@um.ac.ir
Abstract:   (243 Views)
Nowadays, the CNC machining industry uses FMEA approach to improve performance, reduce component failure, and downtime of the machines. FMEA method is one of the most useful approach for the maintenance scheduling and consequently improvement of the reliability. This paper presents an approach to prioritize and assessment the failures of electrical and control components of CNC lathe machine. In this method, the electrical and control components were analyzed independently for every failure mode according to RPN. The results showed that the conventional method by means of a weighted average, generates different RPN values ​​for the subsystems subjected to the study. The best result for Fuzzy FMEA obtained for the 10-scale and centroid defuzzification method. The Fuzzy FMEA sensitivity analysis showed that the subsystem risk level is dependent on O, S, and D indices, respectively. The result of the risk clustering showed that the failure modes can be clustered into three risk groups and a similar maintenance policy can be adopted for all failure modes placed in a cluster. Also, The prioritization of risks could also help the maintenance team to choose corrective actions consciously. In conclusion, the Fuzzy FMEA method was found to be suitably adopted in the CNC machining industry. Finally, this method helped to increase the level of confidence on CNC lathe machine.
Full-Text [PDF 1766 kb]   (142 Downloads)    
Type of Study: Research | Subject: Reliability and Maintenance
Received: 2018/06/12 | Accepted: 2018/10/6 | Published: 2018/10/6

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