Abstract
The robustness of components/products/systems is a concern for both the company that sells them and the consumers who use them. Failure Modes and Effect Analysis (FMEA) which has evolved over 60 years, is a powerful and effective risk identification tool for both design and manufacturing, often combined with Multiple Criteria Decision-Making methods to increase its utility. However, most previous FMEA studies have neglected the interdependence of the failure modes. To address this issue, this study develops a novel method, the TEchnique for Defining the Influential Relationship of Failure Modes, to determine the risk prioritization of the failure modes. The interaction among failure modes is effectively identified and incorporated into the model. The primary analysis procedure can be divided into three parts: (i) the assessment of the initial risk scores of the failure modes; (ii) the definition of the degree of interdependence among the failure modes; and (iii) the integration of the final risk scores based on dependency. The model is used to conduct a case study for a multinational manufacturer of switch mode power supplies as a demonstration case. The practicality of the proposed model was validated through model comparisons and expert feedback. The results show that “an unstable output voltage”, “no power-good signal”, “recession in efficiency”, “burning out of components”, and “the cooling fan does not operate” are the top five risky failure modes. The research findings can be used as the basis for improvement strategies in R&D design and by quality assurance departments to enhance product reliability.
Similar content being viewed by others
Data availability
The authors confirm that the data supporting the findings of this study are available in the article.
References
Boral, S., Howard, I., Chaturvedi, S.K., McKee, K., Naikan, V.N.A.: An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA. Eng. Fail. Anal. 108, 104195 (2020)
Cabanes, B., Hubac, S., Le Masson, P., Weil, B.: Improving reliability engineering in product development based on design theory: the case of FMEA in the semiconductor industry. Res. Eng. Des. 32(3), 309–329 (2021)
Peng, H.M., Wang, X.K., Wang, T.L., Liu, Y.H., Wang, J.Q.: Extended failure mode and effect analysis approach based on hesitant fuzzy linguistic Z-numbers for risk prioritisation of nuclear power equipment failures. J. Intell. Fuzzy Syst. 40, 10489–10505 (2021)
Shaker, F., Shahin, A., Jahanyan, S.: Develo** a two-phase QFD for improving FMEA: an integrative approach. Int. J. Qual. Reliab. Manag. 36(8), 1454–1474 (2019)
Ouyang, L., Yan, L., Han, M., Gu, X.: Survey of FMEA methods with improvement on performance inconsistency. Qual. Reliab. Eng. Int. (2021)
Wang, L., Sun, L., Kang, J., Wang, Y., Wang, H.: Risk identification of FPSO oil and gas processing system based on an improved FMEA approach. Appl. Sci. 11(2), 567–585 (2021)
Wu, X., Wu, J.: The risk priority number evaluation of FMEA analysis based on random uncertainty and fuzzy uncertainty. Complexity 2021, 1–15 (2021)
Chang, T.W., Lo, H.W., Chen, K.Y., Liou, J.J.: A novel FMEA model based on rough BWM and rough TOPSIS-AL for risk assessment. Mathematics 7(10), 874–893 (2019)
Wang, Z., Gao, J.M., Wang, R.X., Chen, K., Gao, Z.Y., Zheng, W.: Failure mode and effects analysis by using the house of reliability-based rough VIKOR approach. IEEE Trans. Reliab. 67, 230–248 (2017)
Di Bona, G., Silvestri, A., Forcina, A., Petrillo, A.: Total efficient risk priority number (TERPN): a new method for risk assessment. J. Risk Res. 21(11), 1384–1408 (2018)
Ayber, S., Erginel, N.: Develo** the neutrosophic fuzzy FMEA method as evaluating risk assessment tool. Adv. Intell. Syst. Comput. 1029, 1130–1137 (2020)
Karatop, B., Taşkan, B., Adar, E., Kubat, C.: Decision analysis related to the renewable energy investments in Turkey based on a fuzzy AHP-EDAS-Fuzzy FMEA approach. Comput. Ind. Eng. 151, 106958 (2021)
Ünver, M., Cil, I.: Material selection by using fuzzy complex proportional assessment. Emerg. Mater. Res. 9(1), 93–98 (2020)
Yucesan, M., Gul, M., Celik, E.: A holistic FMEA approach by fuzzy-based Bayesian network and best–worst method. Complex Intell Syst. 7(3), 1547–1564 (2021)
Murumkar, A.B., Teli, S.N., Loni, R.R.: Framework for reduction of quality cost. IJREAM Special Issue-ICSGUPSTM, 156–162 (2018)
Huang, H., Tong, X., Cai, Y., Tian, H.: Gap between discarding and recycling: estimate lifespan of electronic products by survey in formal recycling plants in China. Resour. Conserv. Recycl. 156, 104700 (2020)
Guinot, J., Evans, D., Badar, M.A.: Cost of quality consideration following product launch in a present worth assessment. Int. J. Qual. Reliab. Manag. 33, 399–413 (2016)
Chen, Y., Kang, Y., Zhao, Y., Wang, L., Liu, J., Li, Y., Li, B.: A review of lithium-ion battery safety concerns: the issues, strategies, and testing standards. J. Energy Chem. 59, 83–99 (2021)
Lo, H.W., Liou, J.J.: A novel multiple–criteria decision–making–based FMEA model for risk assessment. Appl. Soft Comput. 73, 684–696 (2018)
Ilbahar, E., Karaşan, A., Cebi, S., Kahraman, C.: A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Saf. Sci. 103, 124–136 (2018)
Tzeng, G.H., Shen, K.Y.: New Concepts and Trends of Hybrid Multiple Criteria Decision Making. CRC Press, pp. 6–7 (2017)
Escobar, C.A., Chakraborty, D., McGovern, M., Macias, D., Morales-Menendez, R.: Quality 4.0–Green, black and master black belt curricula. Procedia Manuf. 53, 748–759 (2021)
Peterson, J.J., Snee, R.D., McAllister, P.R., Schofield, T.L., Carella, A.J.: Statistics in pharmaceutical development and manufacturing. J. Qual. Technol. 41(2), 111–134 (2009)
Eissa, M.E.A.: Extended application of statistical process control-quantitative risk assessment techniques to monitor surgical site infection rates. Int. Med. 1(4), 225–230 (2019)
Gul, M., Ak, M.F.: A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. J. Clean. Prod. 196, 653–664 (2018)
Braglia, M., Gabbrielli, R., Marrazzini, L.: Risk failure deployment: a novel integrated tool to prioritize corrective actions in failure mode and effects analysis. Qual. Reliab. Eng. Int. 37(2), 433–450 (2021)
Yazdi, M.: Improving failure mode and effect analysis (FMEA) with consideration of uncertainty handling as an interactive approach. Int. J. Interact. Des. Manuf. 13(2), 441–458 (2019)
Catelani, M., Ciani, L., Galar, D., Patrizi, G.: Risk assessment of a wind turbine: a new FMECA-based tool with RPN threshold estimation. IEEE Access 8, 20181–20190 (2020)
Dabbagh, R., Yousefi, S.: A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis. J. Safety Res. 71, 111–123 (2019)
Mgbemena, C.E., Tiwari, A., Xu, Y., Prabhu, V., Hutabarat, W.: Ergonomic evaluation on the manufacturing shop floor: a review of hardware and software technologies. CIRP J. Manuf. Sci. Technol. 30, 68–78 (2020)
Cano-Olivos, P., Hernández-Zitlalpopoca, R., Sánchez-Partida, D., Caballero-Morales, S.O., Martínez-Flores, J.L.: Risk analysis of the supply chain of a tools manufacturer in Puebla, Mexico. JCCM 27(4), 406–413 (2019)
Swarnakar, V., Tiwari, A.K., Singh, A.R.: Evaluating critical failure factors for implementing sustainable lean six sigma framework in manufacturing organization. Int. J. Lean Six Sigma 11(6), 1083–1118 (2020)
Roy, R.B., Mishra, D., Pal, S.K., Chakravarty, T., Panda, S., Chandra, M.G., Misra, S.: Digital twin: current scenario and a case study on a manufacturing process. Int. J. Adv. Manuf. Technol. 107(9), 3691–3714 (2020)
Gupta, N., Tiwari, A., Bukkapatnam, S.T., Karri, R.: Additive manufacturing cyber-physical system: supply chain and risks. IEEE Access 8, 47322–47333 (2020)
Bhargava, C., Sharma, P.K., Senthilkumar, M., Padmanaban, S., Ramachandaramurthy, V.K., Leonowicz, Z., Mitolo, M.: Review of health prognostics and condition monitoring of electronic components. IEEE Access 8, 751633–775183 (2020)
Jiang, N., Zhang, L., Liu, Z.Q., Sun, L., Long, W.M., He, P., Zhao, M.: Reliability issues of lead-free solder joints in electronic devices. Sci. Technol. Adv. Mater. 20(1), 876–901 (2019)
Kumar, S., Anbanandam, R.: Impact of risk management culture on supply chain resilience: an empirical study from Indian manufacturing industry. J. Risk Res. 234(2), 246–259 (2020)
Ullah, M., Sarkar, B.: Recovery-channel selection in a hybrid manufacturing-remanufacturing production model with RFID and product quality. Int. J. Prod. Econ. 219, 360–374 (2020)
Liu, H.C., Chen, X.Q., Duan, C.Y., Wang, Y.M.: Failure mode and effect analysis using multi-criteria decision making methods: a systematic literature review. Comput. Ind. Eng. 135, 881–897 (2019)
Cheshmberah, M., Naderizadeh, A., Shafaghat, A., Nokabadi, M.: An integrated process model for root cause failure analysis based on reality charting, FMEA and DEMATEL. Int. J. Data Netw. Sci. 4(2), 225–236 (2020)
Li, X., Han, Z., Zhang, R., Zhang, Y., Zhang, L.: Risk assessment of hydrogen generation unit considering dependencies using integrated DEMATEL and TOPSIS approach. Int. J. Hydrog. Energy 45(53), 29630–29642 (2020)
Zandi, P., Rahmani, M., Khanian, M., Mosavi, A.: Agricultural risk management using fuzzy TOPSIS analytical hierarchy process (AHP) and failure mode and effects analysis (FMEA). Agriculture 10(11), 504–530 (2020)
Li, Y., Zhu, L.: Risk analysis of human error in interaction design by using a hybrid approach based on FMEA, SHERPA, and fuzzy TOPSIS. Qual. Reliab. Eng. Int. 36(5), 1657–1677 (2020)
Wang, L., Yan, F., Wang, F., Li, Z.: FMEA-CM based quantitative risk assessment for process industries: a case study of coal-to-methanol plant in China. Process. Saf. Environ. Prot. 149, 299–311 (2021)
Akcan, S., Güldeş, M.: Methodology for risk assessment based on grey relational analysis: a case study in the automotive industry. In: 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), IEEE (2020), pp. 1–6.
Fu, Y., Qin, Y., Wang, W., Liu, X., Jia, L.: An extended FMEA model based on cumulative prospect theory and Type-2 intuitionistic fuzzy VIKOR for the Railway Train Risk Prioritization. Entropy 22(12), 1418–1436 (2020)
Rathore, R., Thakkar, J.J., Jha, J.K.: Evaluation of risks in foodgrains supply chain using failure mode effect analysis and fuzzy VIKOR. Int. J. Qual. Reliab. Manag. 38(2), 551–580 (2020)
Nabizadeh, M., Khalilzadeh, M., Ebrahimnejad, S., Ershadi, M.J.: Develo** a fuzzy goal programming model for health, safety and environment risks based on hybrid fuzzy FMEA-VIKOR method. J. Eng. Des. Technol. 19(2), 317–338 (2021)
Wang, Z.L., You, J.X., Liu, H.C., Wu, S.M.: Failure mode and effect analysis using soft set theory and COPRAS method. Int. J. Comput. Intell. Syst. 10(1), 1002–1015 (2017)
Pancholi, N., Bhatt, M.: FMECA-based maintenance planning through COPRAS-G and PSI. J. Qual. Maint. Eng. 24(2), 224–243 (2018)
Ansari, Z.N., Kant, R., Shankar, R.: Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach. Int. J. Sustain. Eng. 13(6), 473–494 (2020)
Zhou, Q., Thai, V.V.: Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction. Saf. Sci. 83, 74–79 (2016)
Panchal, D., Kumar, D.: Integrated framework for behaviour analysis in a process plant. J Loss Prevent Proc. 40, 147–161 (2016)
Fattahi, R., Khalilzadeh, M.: Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Saf. Sci. 102, 290–300 (2018)
Lo, H.W., Liou, J.J., Huang, C.N., Chuang, Y.C.: A novel failure mode and effect analysis model for machine tool risk analysis. Reliab. Eng. Syst. Saf. 183, 173–183 (2019)
Yanilmaz, S., Baskak, D., Yucesan, M., Gul, M.: Extension of FEMA and SMUG models with Bayesian best-worst method for disaster risk reduction. Int. J. Disaster Risk Reduct. 66, 102631 (2021)
Yousefi, S., Valipour, M., Gul, M.: Systems failure analysis using Z-number theory-based combined compromise solution and full consistency method. Appl. Soft Comput. 113, 107902 (2021)
Lo, H.W., Liou, J.J., Yang, J.J., Huang, C.N., Lu, Y.H.: An extended FMEA model for exploring the potential failure modes: a case study of a steam turbine for a nuclear power plant. Complexity 2021 (2021)
Gul, M., Lo, H.W., Yucesan, M.: Fermatean fuzzy TOPSIS-based approach for occupational risk assessment in manufacturing. Complex Intell. Syst. 7(5), 2635–2653 (2021)
Liou, J.J., Liu, P.C., Luo, S.S., Lo, H.W., Wu, Y.Z.: A hybrid model integrating FMEA and HFACS to assess the risk of inter-city bus accidents. Complex Intell. Syst. 1–20 (2022)
Ak, M.F., Yucesan, M., Gul, M.: Occupational health, safety and environmental risk assessment in textile production industry through a Bayesian BWM-VIKOR approach. Stoch Environ Res Risk Assess 36(2), 629–642 (2022)
Chang, K.H.: Generalized multi–attribute failure mode analysis. Neurocomputing 175, 90–100 (2016)
Chai, K.C., Jong, C.H., Tay, K.M., Lim, C.P.: A perceptual computing–based method to prioritize failure modes in failure mode and effect analysis and its application to edible bird nest farming. Appl. Soft Comput. 49, 734–747 (2016)
Safari, H., Faraji, Z., Majidian, S.: Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR. J. Intell. Manuf. 27(2), 475–486 (2016)
Ahmadi, M., Behzadian, K., Ardeshir, A., Kapelan, Z.: Comprehensive risk management using fuzzy FMEA and MCDA techniques in highway construction projects. J. Civ. Eng. Manag. 23(2), 300–310 (2017)
Ahmadi, M., Molana, S.M.H., Sajadi, S.M.: A hybrid FMEA–TOPSIS method for risk management, case study: Esfahan Mobarakeh Steel Company. Int. J. Process. Manag. Benchmarking 7(3), 397–408 (2017)
Chen, J.K.: Prioritization of corrective actions from utility viewpoint in FMEA application. Qual. Reliab. Eng. Int. 33(4), 883–894 (2017)
Ahn, J., Noh, Y., Park, S.H., Choi, B.I., Chang, D.: Fuzzy–based failure mode and effect analysis (FMEA) of a hybrid molten carbonate fuel cell (MCFC) and gas turbine system for marine propulsion. J. Power. Sources 364, 226–233 (2017)
Zhao, H., You, J.X., Liu, H.C.: Failure mode and effect analysis using MULTIMOORA method with continuous weighted entropy under interval-valued intuitionistic fuzzy environment. Soft. Comput. 21(18), 5355–5367 (2017)
Mohsen, O., Fereshteh, N.: An extended VIKOR method based on entropy measure for the failure modes risk assessment: a case study of the geothermal power plant (GPP). Saf. Sci. 92, 160–172 (2017)
Panchal, D., Kumar, D.: Risk analysis of compressor house unit in thermal power plant using integrated fuzzy FMEA and GRA approach. Int. J. Ind. Syst. Eng. 25(2), 228–250 (2017)
Wan, N., Li, L., Ye, C., Wang, B.: Risk assessment in intelligent manufacturing process: a case study of an optical cable automatic arranging robot. IEEE Access 7, 105892–105901 (2019)
De Andrade, J.M., De Leite, A.F.C.S.M., Canciglieri, M.B., De Loures, E.F.R., Canciglieri, O.: A multi-criteria approach for FMEA in product development in industry 4.0. Adv. Transdiscipl. Eng. 12, 311–320 (2020)
Gul, M., Yucesan, M., Celik, E.: A manufacturing failure mode and effect analysis based on fuzzy and probabilistic risk analysis. Appl. Soft Comput. 96, 106689 (2020)
Koncz, A., Johanyák, Z.C., Pokorádi, L.: Fuzzy approaches in failure mode and effect analysis. Int. J. Artif. Intell. 19(1), 56–76 (2021)
Shafiee, M., Enjema, E., Kolios, A.: An integrated FTA-FMEA model for risk analysis of engineering systems: a case study of subsea blowout preventers. Appl. Sci. 9(6), 1192 (2019)
Mandal, S., Maiti, J.: Risk analysis using FMEA: fuzzy similarity value and possibility theory based approach. Expert Syst. Appl. 41(7), 3527–3537 (2014)
Zeng, Y., Li, Y.F., Li, X.Y., Huang, H.Z.: Tolerance-based reliability and optimization design of switched-mode power supply. Qual. Reliab. Eng. Int. 35(8), 2774–2784 (2019)
Karamoozian, A., Wu, D.: A hybrid risk prioritization approach in construction projects using failure mode and effective analysis. Eng. Constr. Archit. Manag. 27(9), 2661–2686 (2020)
Xu, K., Tang, L.C., **e, M., Ho, S.L., Zhu, M.L.: Fuzzy assessment of FMEA for engine systems. Reliab. Eng. Syst. Saf. 75(1), 17–29 (2002)
Gul, M., Ak, M.F.: A modified failure modes and effects analysis using interval-valued spherical fuzzy extension of TOPSIS method: case study in a marble manufacturing facility. Soft. Comput. 25(8), 6157–6178 (2021)
Lo, H.W., Shiue, W., Liou, J.J., Tzeng, G.H.: A hybrid MCDM-based FMEA model for identification of critical failure modes in manufacturing. Soft. Comput. 24(20), 15733–15745 (2020)
Khatai, S., Kumar, R., Sahoo, A.K.: Hard turning assessment on EN31 steel in dry and wet cooling environments using grey-fuzzy hybrid optimization approach. Int. J. Mod. Manuf. Technol. 13(2) (2021)
Khatai, S., Kumar, R., Sahoo, A.K., Panda, A.: Investigation on tool wear and chip morphology in hard turning of EN 31 steel using AlTiN-PVD coated carbide cutting tool. Mater. Today: Proc. 59, 1810–1816 (2022)
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
All authors declare that they have no conflict of interests.
Ethical approval
The authors of this article did not perform any studies with humans or animals.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Liou, J.J.H., Liu, P.C.Y. & Lo, HW. Dependency-based FMEA model for product risk analysis: a case study of a switch mode power supply. Int J Interact Des Manuf (2024). https://doi.org/10.1007/s12008-023-01575-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12008-023-01575-3