A New Hybrid FMECA Model for Prioritizing Failure Modes Using Multi-Criteria Decision Making

• Autorzy: Kahouadji Housseyn Amin , Belkaid Fayçal

Identyfikatory

DOI

10.24425/mper.2025.153926

• Języki publikacji: EN

Abstrakty

EN

This paper is an extension of the conference publication (Kahouadji & Belkaid, 2022). It introduces a new Hybrid Failure Modes, effects, and criticality analysis (FMECA) Model for Prioritizing Failure Modes using Multi-Criteria Decision-Making (MCDM) technique which can serve as a substitute for the conventional risk priority number (RPN) methodology. Our argument is that the RPN method has inherent limitations when it comes to evaluating risks and pinpointing crucial concerns, which can lead to imprecise risk management decisions. The proposed hybrid FMECA combines the strengths of subjective assessments, such as expert judgment and descriptive data, with objective, measurable data such as numerical scores. This integration provides a more comprehensive evaluation of risks and criticality. The hybrid approach incorporates the French repairability index (RI) as a new factor which enhances accuracy and reliability while strengthen the eco-awareness of the risk assessment. We integrate two MCDM (VIKOR & TOPSIS) methods into the hybrid FMECA approach and illustrate its effectiveness through a case study where we identify and prioritize critical issues in a complex system. The results of the study confirm that the hybrid FMECA approach provides a more robust risk management tool compared to the traditional RPN method, making it a valuable technique for engineers and risk managers.

Słowa kluczowe

EN

FMECA; RPN; MCDM; TOPSIS; VIKOR; repairability index

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2025
• Tom: Vol. 16, No. 1
• Strony: 1--19
• Opis fizyczny: Bibliogr. 38 poz., tab., zdj.

Twórcy

autor

Kahouadji Housseyn Amin

• University of Tlemcen, Manufacturing Engineering Laboratory of Tlemcen (MELT) Tlemcen, Algeria, 13000

• https://orcid.org/0009-0002-9151-8253

autor

Belkaid Fayçal

• University of Tlemcen, Manufacturing Engineering Laboratory of Tlemcen, Algeria

• https://orcid.org/0000-0003-3531-3931

Bibliografia

• Ahmed, U., Carpitella, S., & Certa, A. (2021). An integrated methodological approach for optimising complex systems subjected to predictive maintenance. Reliability Engineering & System Safety, 216, 108022.
• Ayob, M.A., Zakaria, W.N.W., & Jalani, J. (2014, August). Forward kinematics analysis of a 5-axis RV-2AJ robot manipulator. In 2014 Electrical Power, Electronics, Communicatons, Control and Informatics Seminar (EECCIS) (pp. 87–92). IEEE.
• Babashamsi, P., Golzadfar, A., Yusoff, N.I.M., Ceylan, H., & Nor, N.G.M. (2016). Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities. International Journal of Pavement Research and Technology, 9(2), 112–120.
• Başhan, V., Demirel, H., & Gul, M. (2020). An FMEAbased TOPSIS approach under single valued neutrosophic sets for maritime risk evaluation: the case of ship navigation safety. Soft Computing, 24(24), 18749–18764.
• Basri, E.I., Razak, I.H.A., Ab-Samat, H., & Kamaruddin, S. (2017). Preventive maintenance (PM) planning: a review. Journal of Quality in Maintenance Engineering.
• Bhattacharjee, P., Dey, V., & Mandal, U.K. (2022). Failure Mode and Effects Analysis (FMEA) using interval number based BWM-MCDM approach: Risk Expected Value (REV) method. Soft Computing, 26(22), 12667–12688.
• Boral, S., Chaturvedi, S.K., Howard, I., Naikan, V.N.A., & McKee, K. (2021). An integrated interval type-2 fuzzy sets and multiplicative half quadratic programmingbased MCDM framework for calculating aggregated risk ranking results of failure modes in FMECA. Process Safety and Environmental Protection, 150, 194–222.
• Bouti, A., & Kadi, D.A. (1994). A state-of-the-art review of FMEA/FMECA. International Journal of reliability, quality and safety engineering, 1(04), 515–543.
• Bowles, J.B., & Peláez, C.E. (1995). Fuzzy logic prioritization of failures in a system failure mode, effects, and criticality analysis. Reliability Engineering & System Safety, 50(2), 203–213.
• Carpitella, S., Certa, A., Izquierdo, J., & La Fata, C.M. (2018). A combined multi-criteria approach to support FMECA analyses: A real-world case. Reliability Engineering & System Safety, 169, 394–402.
• Chundi, V., Raju, S., Waim, A.R., & Swain, S.S. (2022). Priority ranking of road pavements for maintenance using analytical hierarchy process and VIKOR method. Innovative Infrastructure Solutions, 7(1), 1–17.
• Dabous, S.A., Ibrahim, F., Feroz, S., & Alsyouf, I. (2021a). Integration of failure mode, effects, and criticality analysis with multi-criteria decision-making in engineering applications: Part I–Manufacturing industry. Engineering Failure Analysis, 122, 105264.
• Dabous, S.A., Ibrahim, F., Feroz, S., & Alsyouf, I. (2021b). Integration of failure mode, effects, and criticality analysis with multi-criteria decision-making in engineering applications: Part II - Non-manufacturing industries. Engineering Failure Analysis, 122, 105296.
• Di Nardo, M., Murino, T., Osteria, G., & Santillo, L.C. (2022). A New Hybrid Dynamic FMECA with DecisionMaking Methodology: A Case Study in An Agri-Food Company. Applied System Innovation, 5(3), 45.
• Djenadic, S., Tanasijevic, M., Jovancic, P., Ignjatovic, D., Petrovic, D., & Bugaric, U. (2022). Risk evaluation: Brief review and innovation model based on fuzzy logic and MCDM. Mathematics, 10(5), 811.
• Ebadzadeh, F., Monavari, S.M., Jozi, S.A., Robati, M., & Rahimi, R. (2023). An integrated of fuzzy-WASPAS and E-FMEA methods for environmental risk assessment: a case study of petrochemical industry, Iran. Environmental Science and Pollution Research, 1–12.
• Gugaliya, A., Boral, S., & Naikan, V. N. A. (2019). A hybrid decision making framework for modified failure mode effects and criticality analysis: a case study on process plant induction motors. International Journal of Quality & Reliability Management, 36(8), 1266–1283.
• Hu, Y.P., You, X.Y., Wang, L., & Liu, H.C. (2019). An integrated approach for failure mode and effect analysis based on uncertain linguistic GRA-TOPSIS method. Soft Computing, 23, 8801–8814.
• Huang, J., Liu, H.C., Duan, C.Y., & Song, M.S. (2022). An improved reliability model for FMEA using probabilistic linguistic term sets and TODIM method. Annals of Operations Research, 1–24.
• Hwang, C.L., Yoon, K., Hwang, C.L., & Yoon, K. (1981). Methods for multiple attribute decision making. Multiple attribute decision making: methods and applications a state-of-the-art survey, 58–191.
• Jafarpisheh, R., Karbasian, M., & Asadpour, M. (2021). A hybrid reliability-centered maintenance approach for mining transportation machines: a real case in Esfahan. International Journal of Quality & Reliability Management, 38(7), 1550–1575.
• Kahouadji, H., & Belkaid, F. (2022, May). Case study of a Risk Prioritization in Failure Mode Effects and Critical Analysis Using MCDM. In 2022 14th International Colloquium of Logistics and Supply Chain Management (LOGISTIQUA) (pp. 1–6). IEEE.
• Liu, Z., Wang, X., Sun, N., Li, L., Wang, D., & Liu, P. (2021). FMEA using the normalized projection-based TODIM-PROMETHEE II model for blood transfusion. International Journal of Fuzzy Systems, 1–17.
• Lo, H.W., Shiue, W., Liou, J.J., & Tzeng, G.H. (2020). A hybrid MCDM-based FMEA model for identification of critical failure modes in manufacturing. Soft Computing, 24, 15733–15745.
• Murthy, D.N.P., Atrens, A., & Eccleston, J.A. (2002). Strategic maintenance management. Journal of Quality in Maintenance Engineering.
• Mzougui, I., & El Felsoufi, Z. (2020). Combination of DSM and MCDM methods for failure mode and effects analysis. In Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) Volume 3 - Advanced Intelligent Systems for Sustainable Development Applied to Environment, Industry and Economy (pp. 144–161). Springer International Publishing.
• Opricovic, S. (1998). Multicriteria optimization of civil engineering systems. Faculty of civil engineering, Belgrade, 2(1), 5–21.
• Opricovic, S., & Tzeng, G.H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455.
• Özcan, E.C., Ünlüsoy, S., & Eren, T. (2017). A combined goal programming–AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants. Renewable and Sustainable Energy Reviews, 78, 1410–1423.
• Pourmehdi, M., Paydar, M.M., & Asadi-Gangraj, E. (2021). Reaching sustainability through collection center selection considering risk: using the integration of Fuzzy ANP-TOPSIS and FMEA. Soft Computing, 25, 10885–10899.
• Rahnamay Bonab, S., & Osgooei, E. (2022). Environment risk assessment of wastewater treatment using FMEA method based on Pythagorean fuzzy multiplecriteria decision-making. Environment, Development and Sustainability, 1–31.
• Renjith, V.R., Kumar, P.H., & Madhavan, D. (2018). Fuzzy FMECA (failure mode effect and criticality analysis) of LNG storage facility. Journal of loss prevention in the process industries, 56, 537–547.
• Seiti, H., & Hafezalkotob, A. (2019). Developing the RTOPSIS methodology for risk-based preventive maintenance planning: A case study in rolling mill company. Computers & Industrial Engineering, 128, 622–636.
• Singh, J., Singh, S., & Singh, A. (2019). Distribution transformer failure modes, effects and criticality analysis (FMECA). Engineering Failure Analysis, 99, 180–191.
• Singh, R.K., Gupta, A., Kumar, A., & Khan, T.A. (2016). Ranking of barriers for effective maintenance by using TOPSIS approach. Journal of Quality in Maintenance Engineering.
• Stamatis, D.H. (2003). Failure mode and effect analysis: FMEA from theory to execution. Quality Press.
• Voogd, J.H. (1982). Multicriteria evaluation for urban and regional planning. Environmental Science, Engineering, Geography.
• Yu, P.L. (1973). A class of solutions for group decision problems. Management science, 19(8), 936–946.,