Havacılık Sektöründe Sezgisel Bulanık TOPSİS Yöntemiyle Risk Analizi Uygulaması

Abstract

Hata Türü ve Etkileri Analizi (HTEA), birçok sektörde potansiyel hataları tanımlamak, değerlendirmek ve önlemek için sıklıkla kullanılan risk analizi tekniklerinden biridir. HTEA, süreçler ve ürünlerdeki potansiyel risklerin belirlenmesine ve azaltılmasına yardımcı olması ve yaygın olarak kullanılması gibi güçlü yönleri olan analitik bir teknik olmasına rağmen bazı noktalarda eleştirilmiştir. Risk değerlendirmesini yapan uzmanlar ve karar vericiler tarafından, risk faktörlerine 1 ile 10 arasında matematiksel bir sayı atamak kolay değildir. Bu noktada sezgisel bulanık mantık yaklaşımının sunduğu dilsel değişkenlerin kullanılması karar vericilere kolaylık sağlamakta ve risk değerlendirmelerinin doğruluğunu artırmaktadır. Bu çalışma, havacılık sektöründe faaliyet gösteren bir işletmenin üretim süreci boyunca ortaya çıkabilecek risklerini HTEA ile değerlendirmeyi amaçlamaktadır. Risk faktörlerinin göz ardı edilmesi ve risk önceliklerinin doğru belirlenememesi ihtimali göz önünde bulundurularak, çalışmaya sezgisel bulanık mantık yaklaşımı entegre edilmiştir. Bu amaçla risk faktörleri uzmanlar tarafından ağırlıklandırılmıştır. Problem çözümünde Sezgisel Bulanık TOPSIS yöntemi kullanılarak, dilsel değişkenlerin desteğiyle hatalar uzmanlar tarafından önceliklendirilmiştir.

Keywords

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

Risk Analysis Application in Aviation Sector with Intuitionistic Fuzzy TOPSIS Method

Abstract

Failure Mode and Effects Analysis (FMEA) is one of the risk analysis techniques often used in many industries to recognize, assess, and avoid potential failures. Although FMEA is an analytical technique with strengths, such as helping to identify and reduce potential risks in processes and products, and being widely used, it has been criticized at some points. It is not easy to appoint a mathematical number between 1 and 10 to risk factors by the experts and decision makers who make the risk assessment. At this point, the use of linguistic variables offered by the intuitionistic fuzzy logic approach provides convenience to decision makers and increases the accuracy of risk assessments. This study purposes to assess the risks that may arise throughout the production process of a company operating in the aviation industry with FMEA. Considering the possibility that risk factors are ignored and risk priorities cannot be determined correctly, intuitionistic fuzzy logic approach is integrated into the study. For this purpose, risk factors have been weighted by experts. In problem solving, failures have been prioritized by experts with the support of linguistic variables by using the Intuitionistic Fuzzy TOPSIS method.

Keywords

• Risk Analysis
• Failure Prioritization
• Failure Mode and Effects Analysis (FMEA)
• Intuitionistic Fuzzy Logic
• TOPSIS

References

1. Arabsheybani, A., Paydar, M. M., & Safaei, A. S. (2018). An integrated fuzzy MOORA method and FMEA technique for sustainable supplier selection considering quantity discounts and supplier’s risk. Journal of Cleaner Production, 190, 577–591.
2. Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96.
3. Balaraju, J., Govinda Raj, M., & Murthy, C. S. (2019). Fuzzy-FMEA risk evaluation approach for LHD machine-A case study. Journal of Sustainable Mining, 18(4), 257–268.
4. Ben-Daya, M., & Raouf, A. (1996). A revised failure mode and effects analysis model. International Journal of Quality and Reliability Management, 13(1), 43–47.
5. Bowles, J. B. (2004). An assessment of RPN prioritization in a failure modes effects and criticality analysis. Journal of the IEST, 47, 51–56.
6. Braglia, M., Frosolini, M., & Montanari, R. (2003). Fuzzy criticality assessment model for failure modes and effects analysis. International Journal of Quality and Reliability Management, 20(4), 503–524.
7. Certa, A., Enea, M., Galante, G. M., & La Fata, C. M. (2017). ELECTRE TRI-based approach to the failure modes classification on the basis of risk parameters: An alternative to the risk priority number. Computers and Industrial Engineering, 108, 100–110.
8. Chang, C. L., Wei, C. C., & Lee, Y. H. (1999). Failure mode and effects analysis using fuzzy method and grey theory. Kybernetes, 28(9), 1072–1080.

9. Chin, K. S., Wang, Y. M., Ka Kwai Poon, G., & Yang, J. B. (2009). Failure mode and effects analysis using a group-based evidential reasoning approach. Computers and Operations Research, 36(6), 1768–1779.
10. Faghih-Roohi, S., Akcay, A., Zhang, Y., Shekarian, E., & de Jong, E. (2020). A group risk assessment approach for the selection of pharmaceutical product shipping lanes. International Journal of Production Economics, 229(April), 1–13.
11. Fattahi, R., & Khalilzadeh, M. (2018). Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Safety Science, 102(October 2017), 290–300.
12. Garvey, P. R. (2008). Analytical methods for risk management. New York: Chapman and Hall/CRC.
13. Gilchrist, W. (1993). Modelling failure modes and effects analysis. International Journal of Quality & Reliability Management, 10(5), 16–23.
14. Guo, Q., Sheng, K., Wang, Z., Zhang, X., Yang, H., & Miao, R. (2017). Research on element importance of shafting installation based on QFD and FMEA. Procedia Engineering, 174, 677–685.
15. Hu, K. C., & Hsiao, M. W. (2016). Quality risk assessment model for airline services concerning Taiwanese airlines. Journal of Air Transport Management, 53, 177–185.
16. Huang, J., Li, Z., & Liu, H. C. (2017). New approach for failure mode and effect analysis using linguistic distribution assessments and TODIM method. Reliability Engineering and System Safety, 167(January), 302–309.
17. Hwang, C. L. & Yoon, K. (1981). Multiple attributes decision making methods and applications. Berlin: Springer.
18. Jong, C. H., Tay, K. M., & Lim, C. P. (2013). Application of the fuzzy failure mode and effect analysis methodology to edible bird nest processing. Computers and Electronics in Agriculture, 96, 90–108.
19. Kahraman, C., Kaya, I., & Şenvar, Ö. (2013). Healthcare failure mode and effects analysis under fuzziness. Human and Ecological Risk Assessment, 19(2), 538–552.
20. Kutlu, A. C., & Ekmekçioǧlu, M. (2012). Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Systems with Applications, 39(1), 61–67.
21. Liu, H. C., You, J. X., You, X. Y., & Shan, M. M. (2015). A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method. Applied Soft Computing Journal, 28, 579–588.
22. Liu, H. T., & Tsai, Y. lin. (2012). A fuzzy risk assessment approach for occupational hazards in the construction industry. Safety Science, 50(4), 1067–1078.
23. Liu, Y., Kong, Z., & Zhang, Q. (2018). Failure modes and effects analysis (FMEA) for the security of the supply chain system of the gas station in China. Ecotoxicology and Environmental Safety, 164(5), 325–330.
24. Lo, H. W., & Liou, J. J. H. (2018). A novel multiple-criteria decision-making-based FMEA model for risk assessment. Applied Soft Computing Journal, 73, 684–696.
25. Maniram Kumar, A., Rajakarunakaran, S., Pitchipoo, P., & Vimalesan, R. (2018). Fuzzy based risk prioritisation in an auto LPG dispensing station. Safety Science, 101(May 2017), 231–247.
26. Mızrak Özfırat, P. (2014). Bulanık önceli̇klendi̇rme metodu ve hata türü ve etki̇leri anali̇zi̇ni bi̇rleşti̇ren yeni̇ bi̇r ri̇sk anali̇zi̇ yöntemi̇. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 29(4), 755–768.
27. Ng, W. C., Teh, S. Y., Low, H. C., & Teoh, P. C. (2017). The integration of FMEA with other problem solving tools: A review of enhancement opportunities. Journal of Physics: Conference Series, 890(1).
28. Pillay, A., & Wang, J. (2003). Modified failure mode and effects analysis. Reliability Engineering & System Safety, 79, 69–85.
29. Sankar, N. R., & Prabhu, B. S. (2001). Modified approach for prioritization of failures in a system failure mode and effects analysis. International Journal of Quality & Reliability Management, 18(3), 324–335.
30. Sayyadi Tooranloo, H., Ayatollah, A. S., & Alboghobish, S. (2018). Evaluating knowledge management failure factors using intuitionistic fuzzy FMEA approach. Knowledge and Information Systems, 57(1), 183–205.
31. Sayyadi Tooranloo, H., & Ayatollah, A. S. (2016). A model for failure mode and effects analysis based on intuitionistic fuzzy approach. Applied Soft Computing Journal, 49, 238–247.
32. Şenel, M., Şenel, B., & Havle, C. A. (2018). Risk analysis of ports in maritime industry in Turkey using FMEA based intuitionistic fuzzy TOPSIS approach. ITM Web of Conferences, 22, 01018.
33. Shi, S., Fei, H., & Xu, X. (2019). Application of a FMEA method combining interval 2-tuple linguistic variables and grey relational analysis in preoperative medical service process. IFAC-PapersOnLine, 52(13), 1242–1247.
34. Üçkardeş, İ., & Ünal, D. (2012). Risk analizi ve havacılık sektöründe kaza risklerinin incelenmesi. Ç.Ü Fen ve Mühendislik Bilimleri Dergisi, 27(2), 174–181.
35. Ünlükal, C., Şenel, M., & Şenel, B. (2018). Risk assessment with failure mode and effects analysis and grey relational analysis method in plastic injection process. ITM Web of Conferences, 22, 01023.
36. Wang, L. E., Liu, H. C., & Quan, M. Y. (2016). Evaluating the risk of failure modes with a hybrid MCDM model under interval-valued intuitionistic fuzzy environments. Computers and Industrial Engineering, 102, 175–185.
37. Yang, J., Huang, H. Z., He, L. P., Zhu, S. P., & Wen, D. (2011). Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster-Shafer evidence theory under uncertainty. Engineering Failure Analysis, 18(8), 2084–2092.
38. Yazdi, M. (2018). Risk assessment based on novel intuitionistic fuzzy-hybrid-modified TOPSIS approach. Safety Science, 110(March), 438–448.
39. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.
40. Zerenler, M., & Karaboğa, K. (2014). Müşteri memnuniyetinin sağlanmasında hataların önlenmesine yönelik üretim odaklı bir bakış açısı: Poka-Yoke sistemleri. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, Dr. Mehmet YILDIZ Özel Sayısı, 263–276.
41. Zhou, Q., & Thai, V. V. (2016). Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction. Safety Science, 83, 74–79.