Application of Fuzzy Logic in Design Failure Mode and Effects Analysis

Abstract:

Failure Mode and Effects Analysis (FMEA) is one of the basic and the most used techniques of quality management that is used for continuous improvements in product or process designs. While applying this technique, determining the Risk Priority Numbers (RPN), which indicate the levels of risks associated with potential problems, is of prime importance for the success of application. A traditional RPN is obtained as product of three risk factors: occurrence, severity and detection. Values of these factors are generally attained from past experience and this way of risk assessment sometimes leads to inconsistencies and inaccuracies during priority numbering. Fuzzy logic approach is considered a promising solution in order to give a more accurate ranking of potential risks. This paper presented a fuzzy model, in order to assess and rank risks associated to failure modes that could appear in the functioning of a headlining product used in automotive industry.

• Periodical: Applied Mechanics and Materials (Volume 371)
• Pages: 832-836
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.371.832
• Online since: August 2013
• Authors: Nadia Belu, Daniel Constantin Anghel, Nicoleta Rachieru
• Keywords: Effect Analysis, Failure Mode, Fuzzy Set, Quality Assurance, 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, (2008).

[3] H. C., Liu, Liu, L., Liu, N., & Mao, L. X. Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Systems with Applications. 39 (2012) 12926–12934.

DOI: 10.1016/j.eswa.2012.05.031

[4] H. Gargama, S. K. Chaturvedi, Criticality assessment models for failure mode effects and criticality analysis using fuzzy logic. IEEE Transactions on Reliability. 60 (2011) 102–110.

DOI: 10.1109/tr.2010.2103672

[5] M. Braglia, G. Fantoni, M. Frosolini, The house of reliability. International Journal of Quality & Reliability Management. 24 (2007) 420–440.

DOI: 10.1108/02656710710740572

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

[7] R.H. Yeh, M. -H. Hsieh, Fuzzy assessment of FMEA for a sewage plant, Journal of the Chinese Institute of Industrial Engineers. 24, 6 (2007) 505–512.

DOI: 10.1080/10170660709509064

[8] K. -S. Chin, A. Chan, J. -B. Yang, Development of a fuzzy FMEA based product design system, International Journal of Advanced Manufacturing Technology. 36, 7/8 (2008) 633–649.

DOI: 10.1007/s00170-006-0898-3

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