Failure Mode and Effects Analysis on Control Equipment Using Fuzzy Theory

Abstract:

Failure Mode and Effects Analysis is a methodology to evaluate a system, design, process, machine or service for possible ways in which failures (problems, errors, risks and concerns) can occur and it has been used in a wide range of industries. Traditional method uses a Risk Priority Number to evaluate the risk level of a component or process. This is obtained by finding the multiplication of three factors, which are the severity of the failure (S), the probability/occurrence of the failure (O), and the probability of not detecting the failure (D). There are significant efforts which have been made in FMEA literature to overcome the shortcomings of the crisp RPN calculation. Fuzzy logic appears to be a powerful tool for performing a criticality analysis on a system design and prioritizing failure identified in analisys FMEA for corrective actions. In this paper we present a parallel between the typical and the fuzzy computation of RPNs, in order to assess and rank risks associated to failure modes that could appear in the functioning of control equipment.

• Periodical: Advanced Materials Research (Volume 837)
• Pages: 16-21
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.837.16
• Online since: November 2013
• Authors: Nadia Belu, Daniel Constantin Anghel, Nicoleta Rachieru
• Keywords: Control Equipment, Effect, Failure Mode, Fuzzy Set, Risk Evaluation

References

[1] D.H., Stamatis, Failure Mode and Effect Analysis: FMEA from Theory to Execution, ASQC Quality Press, Milwaukee, 53203, (2003).

[2] Chrysler Corporation, Ford Motor Company, General Motors Corporation, Potential Failure Modes and Effects Analysis (FMEA). Reference Manual, 4th ed., (2008).

[3] K.M. Tay, C.P. Lim, Application of fuzzy inference techniques to FMEA, Advances in Intelligent and Soft Computing 34 (2006) 161–171.

DOI: 10.1007/3-540-31662-0_13

[4] A.C.F. Guimaraes, C.M.F. Lapa, Fuzzy inference to risk assessment on nuclear engineering systems, Applied Soft Computing 7 (2007) 17–28.

DOI: 10.1016/j.asoc.2005.06.002

[5] A. Pillay, J. Wang, Modified failure mode and effects analysis using approximate reasoning, Reliability Engineering and System Safety, vol. 79, no. 1, (2003) 69-85.

DOI: 10.1016/s0951-8320(02)00179-5

[6] K. H. Chang, C. H. Cheng, A risk assessment methodology using intuitionistic fuzzy set in FMEA, International Journal of Systems Science, vol. 41, no. 12, (2010) 1457-1471.

DOI: 10.1080/00207720903353633

[7] R. K. Sharma, D. Kumar and P. Kumar, Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modeling, International Journal of Quality and Reliability Management, vol. 22, no. 9, (2005) 986-1004.

DOI: 10.1108/02656710510625248

[8] J.B., Bowles, C.E. Pelaez, Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliab Eng Syst Saf (1995); 50(2): 203-213.

DOI: 10.1016/0951-8320(95)00068-d

[9] L.A. Zadeh, Fuzzy sets, Information and Control 8 (3) (1965) 338–353.

[10] R., Tassinari, Pratique de l'Analyse fonctionnelle, 4e édition Paris: Dunod, (2006).

[11] J.M. Mendel, Fuzzy logic systems for engineering: a tutorial, Proceedings of the IEEE 83 (3) (1995) 345–377.

[12] H. -J. Zimmermann, Fuzzy Set Theory–and its Applications, 4th ed., Kluwer Academic Publishers, Norwell, Massachusetts, USA, (2001).