Failure mode, effects, and criticality analysis (FMECA) has become a fundamental tool for identifying critical failure modes and prioritizing maintenance activities. As part of the analysis, the risk priority number (RPN), a numeric assessment of the risk, has received much attention as it is computed using severity (S), occurrence (O), and detectability (D), which serve as the main criteria for criticality analysis in many practical FMECA cases. In this paper, we assemble and present a data set containing RPN evaluations from 20 real-world cases. We then apply K-Means clustering to identify the most critical failure modes and propose a novel ranking algorithm that prioritizes mitigation actions based on specific criteria for each failure mode. Our experimental results suggest that both clustering and ranking methods can provide effective prioritization for critical failure modes under given assumptions, while our novel ranking algorithm can adapt to general scenarios and provide more accurate prioritization that can help develop effective maintenance strategies to minimize equipment failure risk and optimize maintenance costs.
Clustering Ranking, Risk priority number, Failure mode effects and criticality analysis
Bouti, A., & Kadi, D. (1994). A state-of-the-art review of FMEA/FMECA. International Journal of reliability, quality and safety engineering, 1(04), 515–543.
Catelani, M., Ciani, L., Cristaldi, L., Faifer, M., Lazzaroni, M., & Rinaldi, P. (2011). FMECA technique on photovoltaic module. In 2011 IEEE international instrumentation and measurement technology conference.
Catelani, M., Ciani, L., Galar, D., Guidi, G., Matucci, S., & Patrizi, G. (2021). FMECA assessment for railway safety-critical systems investigating a new risk threshold method. IEEE Access, 9, 86243–86253.
Ciani, L., Guidi, G., & Patrizi, G. (2019). A critical comparison of alternative risk priority numbers in failure modes, effects, and criticality analysis. IEEE Access, 7, 92398–92409.
Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-1(2), 224–227
Dill, R. P., Brown, N., Curtis, R. L., Herrmann, C. R., & Trampus, A. (1963). State-of-the-art reliability estimate of saturn 5 propulsion systems (Tech. Rep. No. 19930075105). NASA Technical Documents.
Dumnic, B., Liivik, E., Popadic, B., Blaabjerg, F., Milicevic, D., & Katic, V. (2020). Comparative analysis of reli ´ ability for string and central inverter pv systems in accordance with the FMECA. In 2020 IEEE 11th international symposium on power electronics for distributed generation systems (PEDG) (pp. 591–596).
El-Dogdog, T. M., El-Assal, A. M., Abdel-Aziz, I. H., & El-Betar, A. A. (2016). Implementation of FMECA and fishbone techniques in reliability centred maintenance planning. International Journal of Innovative Research in Science, Engineering and Technology, 5(11), 18801–18811.
IEEE guide for failure investigation, documentation, analysis, and reporting for power transformers and shunt reactors (Standard). (2015). Institute of Electrical and Electronics Engineers (IEEE).
Keskin, G. A., & Ozkan, C. (2009). An alternative evaluation ¨ of FMEA: Fuzzy ART algorithm. Quality and Reliability Engineering International, 25(6), 647–661.
Khalil, M. M., Cristaldi, L., & Faifer, M. (2014). FMECA analysis for the assessing of maintenance activity for power transformers. In Proceedings of maintenance performance measurement and management (MPMM) conference 2014 (pp. 21–26).
Khorshidi, H. A., Gunawan, I., & Ibrahim, M. Y. (2016). Data-driven system reliability and failure behavior modeling using FMECA. IEEE Transactions on Industrial Informatics, 12(3), 1253–1260.
Liu, H., Deng, X., & Jiang, W. (2017). Risk evaluation in failure mode and effects analysis using fuzzy measure and fuzzy integral. Symmetry, 9(8), 162.
Mohanty, J. K., Hota, I., Sarkar, P., Sahu, A. K., Dash, P. R., & Pradhan, P. K. (2021). FMECA analysis and condition monitoring of kneader in green anode plant of an aluminium smelter. In Advances in mechanical processing and design: Select proceedings of ICAMPD 2019 (pp. 305–317).
Nursanti, E., Sibut, S., Hutabarat, J., & Septiawan, A. (2018). Risk management in subsea pipelines construction project using delphi method, FMECA, and continuous improvement. ARPN Journal of Engineering and Applied Sciences, 13(11).
Pancholi, N., & Bhatt, M. (2017). Quality enhancement in maintenance planning through non-identical FMECA approaches. International Journal for Quality Research, 11(3), 603.
Perez-Ortega, J., Almanza-Ortega, N. N., Vega-Villalobos, ´ A., Pazos-Rangel, R., Zavala-D´ıaz, C., & Mart´ınezRebollar, A. (2019). The k-means algorithm evolution. In Introduction to data science and machine learning.
Procedures for performing a failure mode, effect and critical analysis (Standard). (1949). United States Department of Defense.
Procedures for performing a failure mode, effect and critical analysis (Standard). (1980). United States Department of Defense.
Royer, M., Libessart, M., Dubaele, J. M., Tourneux, P., & Marc¸on, F. (2020). Controlling risks in the compounding process of individually formulated parenteral nutrition: Use of the FMECA method (failure modes, effects, and criticality analysis). Pharmaceutical Technology in Hospital Pharmacy, 4(3-4), 105–112.
Saraswati, D., Marie, I. A., & Witonohadi, A. (2014). Power transformer failures evaluation using failure mode effect and criticality analysis (FMECA) method. Asian Journal of Engineering and Technology, 2(6).
Scriboni, M. (2020). FMECA and FTA analysis for industrial and collaborative robots (Unpublished doctoral dissertation). Politecnico di Torino.
Silva, J., Antunes, G. J., & Vidal, D. F. (2020). Application of the FMECA method to define preventive maintenance strategies in a vacuum system of a PET extruder. In International joint conference on industrial engineering and operations management (IJCIEOM 2020).
Singh, J., Singh, S., & Singh, A. (2019). Distribution transformer failure modes, effects and criticality analysis (FMECA). Engineering Failure Analysis, 99, 180– 191.
Steinhaus, H. (1957). Sur la division des corps materiels en ´ parties. Bull. Acad. Pol. Sci., Cl. III, 4, 801–804.
Tanjung, W. N., Atikah, S. A., Hidayat, S., Ripmiatin, E., Asti, S. S., & Khodijah, R. S. (2019). Risk management analysis using FMECA and ANP methods in the supply chain of wooden toy industry. In IOP conference series: Materials science and engineering (Vol. 528, p. 012007).
Yssaad, B., Khiat, M., & Chaker, A. (2012). Maintenance optimization for equipment of power distribution system based on FMECA method. Acta Electrotehnica, 53(3), 218–223.
Zhai, X. Y., Zhai, Z. P., Lan, Y. Z., Wu, Y. M., Cheng, H. Y., & Zhang, C. C. (2021). System reliability analysis of forage crushing machine based on fuzzy FMECA. IOP Conference Series: Materials Science and Engineering, 1043(2), 022042.
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