Risk Assessment Using the PFDA-FMEA Integrated Method
Abstract
Purpose: The paper aims to introduce risk assessment in new product development as an important activity for a successful new product launch. A practical example is presented to demonstrate the integration of tools Failure Mode and Effect Analysis (FMEA) and Pythagorean Fuzzy Dimensional Analysis (PFDA) at new product development process, which is a machined component.
Methodology/Approach: Individual steps for creating a case study were carried out: create a Subject Matter Expert (SME) team, identify product failure modes, use linguistic values to assess the FMEA, compute and obtain the PFDA-FMEA and determine the product failure modes ranking.
Findings: Minimized uncertainty in the final evaluation of the FMEA and improvement in the decision-making process based on the risks already identified in the new product development process.
Research Limitation/Implication: The PFDA-FMEA method was based on the risk assessment of a machined part development process. Nevertheless, this method can be used for application in many other areas of industry that require high precision in risk analysis.
Originality/Value of paper: The aim of this paper is to reveal a new integrated method in which FMEA, Pythagorean Fuzzy Sets (PFS) and Dimensional Analysis (DA) are coherent in one model.
References
Automotive Industry Action Group (AIAG), 2022. AIAG.org - Automotive Industry Action Group. [online] Available at: < https://www.aiag.org/ > [Accessed 04 May 2022].
Boral, S., Howard, I., Chaturvedi, S.K., McKee, K. and Naikana, V., 2020. An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA. Engineering Failure Analysis, [e-journal] 108, 104195. DOI: 10.1016/j.engfailanal.2019.104195.
Bowles, J.B. and Peláez, C.E., 1995. Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliability Engineering & System Safety, 50(2), pp.203-213.
Cao, T., Zhang, H., Zheng, H., Yang, Y. and Wang, X., 2013. Quantitative HAZOP Risk Analysis for Oil Tanks Using the Fuzzy Set Theory. In: International Pipeline Conference, 2012 9th International Conference. Calgary, Albania, Canada. 24-28 September 2012. ASME. Pp.379-385.
Čepin, M., 2011. Event Tree Analysis. London: Springer.
Česká společnost pro jakost, 2019. Příručka FMEA - analýza možností vzniku vad a jejich následků. Praha: Česká společnost pro jakost.
Dai, W., Maropoulos, P.G., Cheung, W.M. and Tang, X., 2011. Decision-making in product quality based on failure knowledge. International Journal of Product Lifecycle Management, 5(2-4), pp.143-163.
Ferdous, R., Khan, F., Sadiq, R., Amyotte, P. and Veitch, B., 2012. Handling and updating uncertain information in bow-tie analysis. Journal of Loss Prevention in the Process Industries, 25(1), pp.8-19.
García-Aguirre, P.A., Pérez-Domínguez, L., Luviano-Cruz, D., Gómez, E.M., Pérez-Olguin, I.J. and Dávalos-Ramírez, J.O., 2021a. Risk Assessment With Value Added Pythagorean Fuzzy Failure Mode and Effect Analysis for Stakeholders. IEEE Access, 149(9), pp.560-568.
García-Aguirre, P.A., Pérez-Domínguez, L., Luviano-Cruz, D., Noriega, J.J., Gómez, E.M. and Callejas-Cuervo, M., 2021b. PFDA-FMEA, an integrated method improving FMEA assessment in product design. Applied Sciences, [e-journal] 11(4), 1406. DOI: 10.3390/app11041406.
Goyal, A., 2020. A Critical Analysis of Porter’s 5 Forces Model of Competitive Advantage. Journal of Emerging Technologies and Innovative Research, 7(7), pp.149-152.
Huang, J., Jian-Xin, Y., Hu-Chen, L. and Ming-Shun, S., 2020. Failure mode and effect analysis improvement: A systematic literature review and future research agenda. Reliability Engineering & System Safety, 199(C), 106885. DOI: 10.1016/j.ress.2020.106885.
Juhaszova, D., 2013. Failure Analysis in Development & Manufacture for Customer. Quality Innovation Prosperity, [e-journal] 17(2), pp.89-102. DOI: 10.12776/qip.v17i2.203.
Karunathilake, H., Bakhtavar, E., Chhipi-Shrestha, G.K., Mian, H.R., Hewage, K. and Sadiq, R., 2020. Decision making for risk management: A multi-criteria perspective. Methods in Chemical Process Safety, [e-journal] 4, pp.239-287. DOI: 10.1016/bs.mcps.2020.02.004
Kumar, P., Raju, N., Navaneetha, M. and Ijmtst, E., 2021. Reliability Analysis of Dumpers through FMEA-TOPSIS Integration. International Journal for Modern Trends in Science and Technology, [e-journal] 7(9), pp.110-118. DOI: 10.46501/IJMTST0709018.
Lengyel, L., Zgodavová, K. and Bober, P., 2012. Modeling and Simulation of Relocation of a Production in SIMPRO-Q Web Based Educational Environment. International Journal of Advanced Corporate Learning (iJAC), [e-journal] 5(1), pp.26-31. DOI: 10.3991/ijac.v5i1.1878.
Liu, H.-C., Chen, X.-Q., Duan, C.-Y. and Wang, Y.-M., 2019. Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review. Computers & Industrial Engineering, [e-journal] 135, pp.881-897. DOI: 10.1016/j.cie.2019.06.055.
Magalhães, W.R.d. and Lima Junior, F.R., 2021. A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial. Gestão & Produção, [e-journal] 28(4), e5535. DOI: 0.1590/1806-9649-2020v28e5535.
Mihaliková, M., Zgodavová, K., Bober, P. and Špegárová, A., 2021. The Performance of CR180IF and DP600 Laser Welded Steel Sheets under Different Strain Rates. Materials, [e-journal] 14(6), 1553. DOI: 0.3390/ma14061553
Nagyová, A., Pačaiová, H., Gobanová, A. and Turisová, R., 2019. An Empirical Study of Root-Cause Analysis in Automotive Supplier Organisation. Quality Innovation Prosperity, [e-journal] 23(2), pp.34-45. DOI: 10.12776/qip.v23i2.1243.
Qin, J., Xi, Y. and Pedrycz, W., 2020. Failure mode and effects analysis (FMEA) for risk assessment based on interval type-2 fuzzy evidential reasoning method. Applied Soft Computing, [e-journal] 89(C). Available at: < https://dl.acm.org/doi/abs/10.1016/j.asoc.2020.106134 > [Accessed 21 November 2022]. DOI: 10.1016/j.asoc.2020.106134.
Sabaei, D., Erkoyuncu, J. and Roy, R., 2015. A Review of Multi-criteria Decision Making Methods for Enhanced Maintenance Delivery. Procedia CIRP, 37, pp.30-35.
Sarkar, B., 2011. Fuzzy decision making and its applications in cotton fibre grading. Soft Computing in Textile Engineering, [e-journal] 2011, pp.353-383. DOI: 10.1533/9780857090812.5.353.
Solc, M., Markulik, S., Petrik, J., Balazikova, M., Blasko, P., Kliment, J. and Bezak, M., 2021. Application of FTA Analysis for Calculation of the Probability of the Failure of the Pressure Leaching Process. Applied Sciences, [e-journal] 11(15), 6731. DOI: 10.3390/app11156731.
Tixier, J., Dusserre, G., Salvi, O. and Gaston, D., 2002. Review of 62 risk analysis methodologies of industrial plants. Journal of Loss Prevention in the Process Industries, 15(4), pp.291-303.
Turisova, R. and Kadarova, J., 2015. Increasing the accuracy of the FMEA method. Investment Management and Financial Innovations, 12(4), pp.176-186.
Tzeng, G.-H. and Huang, J.-J., 2014. Fuzzy Multiple Objective Decision Making. Boca Raton: Taylor Francis Group.
VDA, 2022. VDA: German Association of the Automotive Industry. [Online] Available at: < https://www.vda.de/en > [Accessed 05 April 2022].
Villa Silva, A., Pérez Dominguez, L., Martínez Gómez, E., Alvarado-Iniesta, A. and Pérez Olguín, I., 2019. Dimensional analysis under pythagorean fuzzy approach for supplier selection. Symmetry, [e-journal] 11(3), 336. DOI: 10.3390/sym11030336.
Yager, R., 2013. Pythagorean fuzzy subsets. In: IEEE, Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS). Edmonton, Canada. 24-28 June 2013. IEEE. pp.57-61. DOI: 10.1109/IFSA-NAFIPS.2013.6608375.
Yucesan, M., Gul, M. and Celik, E., 2021. A holistic FMEA approach by fuzzy based Bayesian network. Complex & Intelligent Systems, [e-journal] 7(1), 18p. DOI: 10.1007/s40747-021-00279-z.
Zhang, H., Dong, Y., Xiao, J., Chiclana, F. and Herrera-Viedma, E., 2020. Personalized individual semantics-based approach for linguistic failure modes and effects analysis with incomplete preference information. Quality & Reliability Engineering, [e-journal] 52(11), pp.1275-1296. DOI: 10.1080/24725854.2020.1731774.
Boral, S., Howard, I., Chaturvedi, S.K., McKee, K. and Naikana, V., 2020. An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA. Engineering Failure Analysis, [e-journal] 108, 104195. DOI: 10.1016/j.engfailanal.2019.104195.
Bowles, J.B. and Peláez, C.E., 1995. Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliability Engineering & System Safety, 50(2), pp.203-213.
Cao, T., Zhang, H., Zheng, H., Yang, Y. and Wang, X., 2013. Quantitative HAZOP Risk Analysis for Oil Tanks Using the Fuzzy Set Theory. In: International Pipeline Conference, 2012 9th International Conference. Calgary, Albania, Canada. 24-28 September 2012. ASME. Pp.379-385.
Čepin, M., 2011. Event Tree Analysis. London: Springer.
Česká společnost pro jakost, 2019. Příručka FMEA - analýza možností vzniku vad a jejich následků. Praha: Česká společnost pro jakost.
Dai, W., Maropoulos, P.G., Cheung, W.M. and Tang, X., 2011. Decision-making in product quality based on failure knowledge. International Journal of Product Lifecycle Management, 5(2-4), pp.143-163.
Ferdous, R., Khan, F., Sadiq, R., Amyotte, P. and Veitch, B., 2012. Handling and updating uncertain information in bow-tie analysis. Journal of Loss Prevention in the Process Industries, 25(1), pp.8-19.
García-Aguirre, P.A., Pérez-Domínguez, L., Luviano-Cruz, D., Gómez, E.M., Pérez-Olguin, I.J. and Dávalos-Ramírez, J.O., 2021a. Risk Assessment With Value Added Pythagorean Fuzzy Failure Mode and Effect Analysis for Stakeholders. IEEE Access, 149(9), pp.560-568.
García-Aguirre, P.A., Pérez-Domínguez, L., Luviano-Cruz, D., Noriega, J.J., Gómez, E.M. and Callejas-Cuervo, M., 2021b. PFDA-FMEA, an integrated method improving FMEA assessment in product design. Applied Sciences, [e-journal] 11(4), 1406. DOI: 10.3390/app11041406.
Goyal, A., 2020. A Critical Analysis of Porter’s 5 Forces Model of Competitive Advantage. Journal of Emerging Technologies and Innovative Research, 7(7), pp.149-152.
Huang, J., Jian-Xin, Y., Hu-Chen, L. and Ming-Shun, S., 2020. Failure mode and effect analysis improvement: A systematic literature review and future research agenda. Reliability Engineering & System Safety, 199(C), 106885. DOI: 10.1016/j.ress.2020.106885.
Juhaszova, D., 2013. Failure Analysis in Development & Manufacture for Customer. Quality Innovation Prosperity, [e-journal] 17(2), pp.89-102. DOI: 10.12776/qip.v17i2.203.
Karunathilake, H., Bakhtavar, E., Chhipi-Shrestha, G.K., Mian, H.R., Hewage, K. and Sadiq, R., 2020. Decision making for risk management: A multi-criteria perspective. Methods in Chemical Process Safety, [e-journal] 4, pp.239-287. DOI: 10.1016/bs.mcps.2020.02.004
Kumar, P., Raju, N., Navaneetha, M. and Ijmtst, E., 2021. Reliability Analysis of Dumpers through FMEA-TOPSIS Integration. International Journal for Modern Trends in Science and Technology, [e-journal] 7(9), pp.110-118. DOI: 10.46501/IJMTST0709018.
Lengyel, L., Zgodavová, K. and Bober, P., 2012. Modeling and Simulation of Relocation of a Production in SIMPRO-Q Web Based Educational Environment. International Journal of Advanced Corporate Learning (iJAC), [e-journal] 5(1), pp.26-31. DOI: 10.3991/ijac.v5i1.1878.
Liu, H.-C., Chen, X.-Q., Duan, C.-Y. and Wang, Y.-M., 2019. Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review. Computers & Industrial Engineering, [e-journal] 135, pp.881-897. DOI: 10.1016/j.cie.2019.06.055.
Magalhães, W.R.d. and Lima Junior, F.R., 2021. A model based on FMEA and Fuzzy TOPSIS for risk prioritization in industrial. Gestão & Produção, [e-journal] 28(4), e5535. DOI: 0.1590/1806-9649-2020v28e5535.
Mihaliková, M., Zgodavová, K., Bober, P. and Špegárová, A., 2021. The Performance of CR180IF and DP600 Laser Welded Steel Sheets under Different Strain Rates. Materials, [e-journal] 14(6), 1553. DOI: 0.3390/ma14061553
Nagyová, A., Pačaiová, H., Gobanová, A. and Turisová, R., 2019. An Empirical Study of Root-Cause Analysis in Automotive Supplier Organisation. Quality Innovation Prosperity, [e-journal] 23(2), pp.34-45. DOI: 10.12776/qip.v23i2.1243.
Qin, J., Xi, Y. and Pedrycz, W., 2020. Failure mode and effects analysis (FMEA) for risk assessment based on interval type-2 fuzzy evidential reasoning method. Applied Soft Computing, [e-journal] 89(C). Available at: < https://dl.acm.org/doi/abs/10.1016/j.asoc.2020.106134 > [Accessed 21 November 2022]. DOI: 10.1016/j.asoc.2020.106134.
Sabaei, D., Erkoyuncu, J. and Roy, R., 2015. A Review of Multi-criteria Decision Making Methods for Enhanced Maintenance Delivery. Procedia CIRP, 37, pp.30-35.
Sarkar, B., 2011. Fuzzy decision making and its applications in cotton fibre grading. Soft Computing in Textile Engineering, [e-journal] 2011, pp.353-383. DOI: 10.1533/9780857090812.5.353.
Solc, M., Markulik, S., Petrik, J., Balazikova, M., Blasko, P., Kliment, J. and Bezak, M., 2021. Application of FTA Analysis for Calculation of the Probability of the Failure of the Pressure Leaching Process. Applied Sciences, [e-journal] 11(15), 6731. DOI: 10.3390/app11156731.
Tixier, J., Dusserre, G., Salvi, O. and Gaston, D., 2002. Review of 62 risk analysis methodologies of industrial plants. Journal of Loss Prevention in the Process Industries, 15(4), pp.291-303.
Turisova, R. and Kadarova, J., 2015. Increasing the accuracy of the FMEA method. Investment Management and Financial Innovations, 12(4), pp.176-186.
Tzeng, G.-H. and Huang, J.-J., 2014. Fuzzy Multiple Objective Decision Making. Boca Raton: Taylor Francis Group.
VDA, 2022. VDA: German Association of the Automotive Industry. [Online] Available at: < https://www.vda.de/en > [Accessed 05 April 2022].
Villa Silva, A., Pérez Dominguez, L., Martínez Gómez, E., Alvarado-Iniesta, A. and Pérez Olguín, I., 2019. Dimensional analysis under pythagorean fuzzy approach for supplier selection. Symmetry, [e-journal] 11(3), 336. DOI: 10.3390/sym11030336.
Yager, R., 2013. Pythagorean fuzzy subsets. In: IEEE, Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS). Edmonton, Canada. 24-28 June 2013. IEEE. pp.57-61. DOI: 10.1109/IFSA-NAFIPS.2013.6608375.
Yucesan, M., Gul, M. and Celik, E., 2021. A holistic FMEA approach by fuzzy based Bayesian network. Complex & Intelligent Systems, [e-journal] 7(1), 18p. DOI: 10.1007/s40747-021-00279-z.
Zhang, H., Dong, Y., Xiao, J., Chiclana, F. and Herrera-Viedma, E., 2020. Personalized individual semantics-based approach for linguistic failure modes and effects analysis with incomplete preference information. Quality & Reliability Engineering, [e-journal] 52(11), pp.1275-1296. DOI: 10.1080/24725854.2020.1731774.
Authors
Čička, M., Turisová, R., & Čičková, D. (2022). Risk Assessment Using the PFDA-FMEA Integrated Method. Quality Innovation Prosperity, 26(3), 112–134. https://doi.org/10.12776/qip.v26i3.1772
This work is licensed under a Creative Commons Attribution 4.0 International License.