USE OF THE FUZZY SWARA METHOD IN FAILURE MODE EFFECT ANALYSIS: CASE OF AUTOMOTIVE INDUSTRY

Abstract

Failure Mode Effects Analysis (FMEA) is a technique that enables the determination of the errors that may occur in the enterprises, taking precautions and reporting them. Probability, severity and detectability values are assigned to each of the errors identified in FMEA studies, and the Risk Priority Number (RPN) is calculated by multiplying these values. The calculated RPN values are used to take precautions against the said errors. However, there are some methodological weaknesses such as taking the values assigned to probability, severity and detectability from numerical tables corresponding to linguistic expressions and giving equal importance to each risk factor. In recent years, fuzzy expert-oriented approaches have begun to be used to overcome these weaknesses. In this study, the Fuzzy SWARA method was used to weight the risk factors in the FMEA study, which was carried out within the scope of a product selected together with the quality team of a company operating in the automotive sector. According to the results obtained, the company's quality team was informed about which error reason and type should be handled and resolved with priority, together with the FMEA study, which integrated new methods.

Keywords

• Failure Mode Effects Analysis (FMEA)
• Fuzzy Logic
• Fuzzy FMEA
• Fuzzy SWARA
• Fuzzy Risk Prioritization

HATA TÜRÜ VE ETKİLERİ ANALİZİNDE BULANIK SWARA YÖNTEMİNİN KULLANIMI: OTOMOTİV SEKTÖRÜ ÖRNEĞİ

Abstract

Hata Türü ve Etkileri Analizi (HTEA), işletmelerde oluşabilecek hataların önceden tespit edilerek, önlem alınmasını ve raporlanmasını sağlayan bir tekniktir. HTEA çalışmalarında belirlenen hataların her birine olasılık, şiddet ve tespit edilebilirlik değerleri atanmakta ve bu değerlerin çarpılmasıyla Risk Öncelik Sayısı (RÖS) hesaplanmaktadır. Söz konusu hatalara yönelik önlem alınmasında hesaplanan RÖS değerlerinden faydalanılmaktadır. Bununla birlikte olasılık, şiddet ve tespit edilebilirliğe atanan değerlerin dilsel ifadelere karşılık gelen sayısal tablolardan alınması ve her bir risk faktörüne eşit önem verilmesi gibi yönteme dönük bazı zayıflıklar bulunmaktadır. Son yıllarda bu zayıflıkların giderilmesinde birçok çalışmalar yapılmış olup, bulanık uzman odaklı yaklaşımlardan yararlanılmaya başlanmıştır. Bu çalışmada, otomotiv sektöründe faaliyet gösteren bir firmanın kalite ekibi ile birlikte seçilen bir ürün kapsamında yapılan HTEA çalışmasında risk faktörlerinin ağırlıklandırılmasında Bulanık SWARA yönteminden yararlanılmıştır. Elde edilen sonuçlara göre firmanın kalite ekibine yeni yöntemler entegre edilmiş HTEA çalışması ile birlikte, hangi hata nedeni ve türünün öncelikli olarak ele alınması ve çözülmesi gerektiği hakkında bilgilendirme yapılmıştır.

Keywords

• Hata Türü ve Etkileri Analizi (HTEA)
• Bulanık Mantık
• Bulanık HTEA
• Bulanık SWARA
• Bulanık Risk Önceliklendirme

Thanks

Bu çalışma kapsamında örnek uygulama verilerinin sağlanması ve birlikte çalışılması hususunda desteklerini esirgemeyen otomotiv sektöründeki firma ve kalite ekibine desteklerinden dolayı teşekkürlerimizi sunarız.

References

1. Akcan, S. and Tas_, M.A. (2019), “Green supplier evaluation with SWARA-TOPSIS integrated method to reduce ecological risk factors”, Environmental Monitoring and Assessment, Vol. 191 No. 12, p. 736.
2. Baykal, N ve Beyan, T. (2004), “Bulanık Mantık İlke Ve Temelleri”, Bıçaklar Kitabevi, Ankara.
3. Bhalaji, R., Bathrinath, S. and Saravanasankar, S. (2020), “An F-PROMETHEE technique for analysing the risk factors in green manufacturing”, Management Science and Engineering, Vol. 764 No. 1, p. 012015.
4. Braglia, M., Frosolini, M., & Montanari, R. (2003), “Fuzzy TOPSIS approach for failure mode, effects and criticality analysis”, Quality and Reliability Engineering International, 19, 425–443.
5. Chen, Z., Feng, K.M., Zhang, G.S., Yuan, T. ve Pan, C.H., (2008), “Preliminary safety research for CH HCSB TBM based on FMEA method”, Fusion Engineering and Design, Vol. 83, 743–746.
6. Chu M.T., Shyu J., Tzeng G.H. ve Khosla R. (2007), “Comparison Among Three Analytical Methods for Knowledge Communities Group Decision Analysis”, Expert Systems with Applications, Vol. 33, No:4, 1011-1024.
7. Ebeling, C. (2000), “An Introduction to Reliability and Maintainability Engineering”, Tata McGraw-Hill Company Ltd, New York, USA.
8. Ghandi, M. and Roozbahani, A. (2020), “Risk management of drinking water supply in critical conditions using fuzzy PROMETHEE V technique”, Water Resources Management, Vol. 34 No. 2, pp. 595-615.

9. Ghorabaee, M.K., Amiri, M., Zavadskas, E.K. and Antucheviciene, J. (2018), “A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations”, Archives of Civil and Mechanical Engineering, Vol. 18 No. 1, pp. 32-49.
10. Gilchrist, W. (1993), “Modeling failure mode and effect analysis”, International Journal of Quality & Reliability Management, Vol. 10, 16-23.
11. Jafarzadeh Ghoushchi, S., Ab Rahman, M.N., Raeisi, D., Osgooei, E. and Jafarzadeh Ghoushji, M. (2020), “Integrated decision-making approach based on SWARA and GRA methods for the prioritization of failures in solar panel systems under Z-Information”, Symmetry, Vol. 12 No. 2, p. 310.
12. Khalilzadeh, M., Ghasemi, P., Afrasiabi, A. And Shakeri, H. (2020), “Hybrid fuzzy MCDM and FMEA integrating with linear programming approach for the health and safety executive risks: a case study”, Journal of Modelling in Management, 1746-5664.
13. Kiani, R.M., Goh, M. and Zarbakhshnia, N. (2017), “Sustainable third-party reverse logistic provider selection with fuzzy SWARA and fuzzy MOORA in plastic industry”, The International Journal of Advanced Manufacturing Technology, Heidelberg Vol. 91, Iss. 5-8, 2017: 2401-2418.
14. Klir, G.J. ve Yuan, B. (1995), “Fuzzy Sets and Fuzzy Logic: Theory and Application”, Prentice- Hall, Englewood Cliffs, NJ.
15. Koulinas, G., Marhavilas, P., Demesouka, O., Vavatsikos, A. and Koulouriotis, D. (2019), “Risk analysis and assessment in the worksites using the fuzzy-analytical hierarchy process and a quantitative technique–a case study for the Greek construction sector”, Safety Science, Vol. 112, pp. 96-104.
16. Liu, H.C. (2019), “FMEA using cloud model and PROMETHEE method and its application to emergency department”, Improved FMEA Methods for Proactive Healthcare Risk Analysis, Springer Singapore, Singapore.
17. Liu, H.C., You, J.X., You, X.Y. and Shan, M.M. (2014) “A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method” Applied Soft Computing, Volume 28, Pages 579-588.
18. Mete, S., Serin, F., Oz, N.E. and Gul, M. (2019), “A decision-support system based on Pythagorean fuzzy VIKOR for occupational risk assessment of a natural gas pipeline construction”, Journal of Natural Gas Science and Engineering, Vol. 71, p. 102979.
19. O’Connor, P.D.T. (2000), “Practical Reliability Engineering”, Heyden, London.
20. Oprıcovıc, S. (2011), “Fuzzy VIKOR with an Application to Water Resources Planning”, Expert Systems with Applications, Vol. 38, 12983-12990.
21. Pillay, A. ve Wang, J. (2003), “Modified failure mode and effects analysis using approximate reasoning”, Reliability Engineering and System Safety, Vol. 79, 69-85.
22. Poyraz, P. (2021), “Tedarik zinciri risk yönetiminde süreç aşamalı bulanık çok kriterli karar verme yöntemleri ile hata analizi”, Lisansüstü Eğitim Enstitüsü, Endüstri Mühendisliği Ana Bilim Dalı, Yüksek Lisans Tezi.
23. Rezaee, M.J., Yousefi, S., Eshkevari, M., Valipour, M. and Saberi, M. (2020), “Risk analysis of health, safety and environment in chemical industry integrating linguistic FMEA, fuzzy inference system and fuzzy DEA”, Stochastic Environmental Research and Risk Assessment, Vol. 34 No. 1, pp. 201-218.
24. Ross, T.J. (1995), “Fuzzy Logic with Engineering Applications”, McGraw-Hill, New York, NY.
25. Sharma, R. (2005), “Fuzzy logic methodology to prioritize failure causes in FMEA”, Proceedings of International Conf. on Emerging Technologies, ICET- 2004, Allied Pub., New Delhi, 298-306.
26. Song,W., Ming, X., Wu Z. and Zhu, B. (2013) “Failure modes and effects analysis using integrated weight-based fuzzy TOPSİS” International Journal of Computer Integrated Manufacturing, 26:12, 1172-1186.
27. Stanujkic, D., Karabasevic, D. ve Zavadskas, E.K. (2015), “A framework fort he selection of a packaging desing based on the SWARA method”, Inzirine Ekonomika-Engineering Economics, 26(2), 181-187.
28. Sumrit, D. (2020), ‘’Supplier Selection for Vendor-Managed Inventory in Healthcare Using Fuzzy Multi-Criteria Decision Making’’, Decision Science Letters, 9 (2), 233-256.
29. Tabaraee, E., Ebrahimnejad, S. and Bamdad, S. (2017), “Evaluation of power plants to prioritise the investment projects using fuzzy PROMETHEE method”, International Journal of Sustainable Energy, Vol. 37 No. 10, pp. 941-955.
30. Tay, K. ve Lim C. (2006), “Fuzzy FMEA With A Guided Rules Reduction System For Prioritization of Failures”,International Journal of Quality and Reliability Management, Vol. 8, 1047-1066.
31. Terano, T., Asai, K. ve Sugeno, M. (1987), “Fuzzy Systems Theory and its Application”, Academic Press, San Diego, CA.
32. Wu, X and Wu, J. (2021), “The Risk Priority Number Evaluation of FMEA Analysis Based on Random Uncertainty and Fuzzy Uncertainty”, Hindawi Complexity, Vol. 2021, 1-15.
33. Xiao, N., Huang, H.Z.,Li,Y., He, L. and Jin, T. (2011), “Multiple failure modes analysis and weighted risk priority number evaluation in FMEA”, Engineering Failure Analysis, Vol. 18, 1162-1170.
34. Xu, K. ve Tang, L.C. (2002), “Fuzzy assessment of FMEA for engine systems”, Reliability Engineering & System Safety, Vol. 75, 17-29.
35. Zadeh, L. (1965), “Fuzzy sets”, IEEE Information and Control, Vol 8, 338-53.
36. Zarbakhshnia, N., Soleimani, H. and Ghaderi, H. (2018), “Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria”, Applied Soft Computing, Vol. 65, pp. 307-319.
37. Zhang, H.-J., Zhou, Y. and Gan, Q.-H. (2019), “An extended PROMETHEE-II-Based risk prioritization method for equipment failures in the geothermal power plant”, International Journal of Fuzzy Systems, Vol. 21 No. 8, pp. 2490-2509.
38. Zhu, J., Shuai, B., Li, G., Chin, K.-S. and Wang, R. (2020), “Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context”, Journal of Loss Prevention in the Process Industries, Vol. 64, p. 104048.
39. Zimmermann, H. (1996), “Fuzzy Set Theory and its Applications”, Baskı 3, Kluwer Academic Pub., London.