Title of article :
Using Fuzzy FMEA Approach to Improve Decision-Making Process in CNC Machine Electrical and Control Equipment Failure Prediction
Author/Authors :
visi, ali Department of Biosystems Engineering - Ferdowsi University of Mashhad, Mashhad, Iran , rohani, abas Department of Biosystems Engineering - Ferdowsi University of Mashhad, Mashhad, Iran , tabasizadeh, mohammad Department of Biosystems Engineering - Ferdowsi University of Mashhad, Mashhad, Iran
Abstract :
Reliability and safety in the process industry, such as computer
numerical control (CNC) machining industry, are the most
important key success factors in upgrading availability and
preventing catastrophic failures. Failure Mode and Effects
Analysis (FMEA) method is one of the most useful approaches to
the maintenance scheduling and, consequently, improvement of
the reliability. This paper presents an approach to prioritize and
assess 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 risk priority number (RPN). The results showed that
the conventional method by means of a weighted average
generated different RPN values for the subsystems subjected to the
study. The best result for Fuzzy FMEA was obtained for the 10-
scale and centroid defuzzification method. The Fuzzy FMEA
sensitivity analysis showed that the subsystem risk level was
dependent on occurrence (O), severity (S), and detection (D)
indices, respectively. The result of the risk clustering showed that
the failure modes could be clustered into three risk groups, and a
similar maintenance policy could be adopted for all failure modes
placed in a cluster. In addition, 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 increase the level of confidence on CNC lathe
machine.
Keywords :
Fuzzy FMEA , Risk priority number , CNC Lathe Machine , Sensitivity analysis , Risk clustering
Journal title :
Astroparticle Physics