Document Type : Research Paper

Author

Industrial Engineering and Management, Khulna University of Engineering and Technology, Khulna, Bangladesh.

Abstract

FMEA (Failure Mode and Effect Analysis) refers to a proactive quality tool that enables the identification and prevention of the potential failure modes of a product or process. However, in executing traditional FMEA, the difficulties such as vague information, relative importance ratings, decisions on same ratings, and opinion difference among experts arise which reduce the validity of the results. This paper presents a fuzzy logic based FMEA depending on fuzzy IF-THEN rules over traditional FMEA to make it precise and give proper maintenance decision. Here, the Risk Priority Number (RPN) is calculated and compared to the Fuzzy Risk Priority Number (FRPN) to give maintenance decision. Furthermore, the FMEA of Reach Stacker Crane (RST) is presented to demonstrate the proposed Fuzzy FMEA.

Keywords

Main Subjects

[1]  Yeh, R. H., & Hsieh, M. H. (2007). Fuzzy assessment of FMEA for a sewage plant. Journal of the Chinese institute of industrial engineers24(6), 505-512.
[2]  Xu, K., Tang, L. C., Xie, M., Ho, S. L., & Zhu, M. L. (2002). Fuzzy assessment of FMEA for engine systems. Reliability engineering & system safety75(1), 17-29.
[3]  Guimarães, A. C. F., & Lapa, C. M. F. (2004). Fuzzy FMEA applied to PWR chemical and volume control system. Progress in Nuclear Energy44(3), 191-213.
[4]  Xu, K., Tang, L. C., Xie, M., Ho, S. L., & Zhu, M. L. (2002). Fuzzy assessment of FMEA for engine systems. Reliability engineering & system safety75(1), 17-29.
[5]  Bell, D., Cox, L., Jackson, S., & Schaefer, P. (1992, January). Using causal reasoning for automated failure modes and effects analysis (FMEA). Proceedings of annual reliability and maintainability symposium (pp. 343-353). Las Vegas, NV, USA, USA: IEEE.
[6]  Wang, J., Ruxton, T., & Labrie, C. R. (1995). Design for safety of engineering systems with multiple failure state variables. Reliability engineering & system safety50(3), 271-284.
[7]  Bowles, J. B., & Peláez, C. E. (1995). Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliability engineering & system safety50(2), 203-213.
[8]  Quin, S., & Widera, G. E. O. (1996). Uncertainty analysis in quantitative risk assessment. Journal of pressure vessel technology118(1), 121-124.
[9]  El-Shal, S. M., & Morris, A. S. (2000). A fuzzy rule-based algorithm to improve the performance of statistical process control in quality systems. Journal of intelligent & fuzzy systems9(3, 4), 207-223.
[10] He, D., & Adamyan, A. (2001, December). An impact analysis methodology for design of products and processes for reliability and quality. Proceedings of the ASME design engineering technical conference (pp. 209-217). Pittsburgh, PA, United States.
[11] Capunzo, M. A. R. I. O., Cavallo, P. I. E. R. P. A. O. L. O., Boccia, G. I. O. V. A. N. N. I., Brunetti, L. U. I. G. I., & Pizzuti, S. A. N. T. E. (2004). A FMEA clinical laboratory case study: how to make problems and improvements measurable. Clinical leadership and management review18(1), 37-41.
[12] Lee, B. H. (2001). Using Bayes belief networks in industrial FMEA modeling and analysis. Proceedings of annual reliability and maintainability symposium. International symposium on product quality and integrity (pp. 7-15). Philadelphia, PA, USA, USA: IEEE.
[13] Dittmann, L., Rademacher, T., & Zelewski, S. (2004, August). Performing FMEA using ontologies. 18th international workshop on qualitative reasoning (pp. 209-216). Northwestern University, Evanston, Illinois, USA.
[14] Kandel, A. (1986). Fuzzy mathematical techniques with applications. Addison-Wesley.
[15] Quin, S., & Widera, G. E. O. (1996). Uncertainty analysis in quantitative risk assessment. Journal of pressure vessel technology118(1), 121-124.