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Integrated Risk Assessment Analysis with Fuzzy Logic

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DOI: 10.23977/msom.2022.030402 | Downloads: 11 | Views: 572


Betül Aktürk 1, Safiye Turgay 1


1 Dept. of Ind. Eng, Sakarya University, Sakarya, Turkey

Corresponding Author

Betül Aktürk


In a developing business, it has a very important to share in terms of competitive advantage by detecting and directing the errors before occur. There are many methods in the literature for the early detection and prioritization of these failures. Failure modes and effects analysis (FMEA) is also a common method of choice. The uncertainty and flexibility problem arising from error types analysis has been eliminated by integrating fuzzy FMEA. The probability, severity, and discoverability values determined for each error were examined with error types, effects and fuzzy logic methods. Probability, severity, and discoverability values are considered and analyzed. Each method was listed according to the determined risk process network values and expert opinion, and comparisons were made between the methods.


FMEA, Fuzzy logic, Risk analysis, Error Mode and Effect Analysis, Fuzzy sets, Uncertainty


Betül Aktürk, Safiye Turgay, Integrated Risk Assessment Analysis with Fuzzy Logic. Manufacturing and Service Operations Management (2022) Vol. 3: 8-18. DOI:


[1] Abdelgawad, M., &Fayek, A. R. (2010). Risk Management İn the Construction İndustry Using Combined Fuzzy FMEA and Fuzzy AHP. Journal of Construction Engineering and Management, 136(9), 1028-1036
[2] Aktağ H., Çağman N. (2005) Fuzzy and Approximated Sets, Çankaya University Journal of Science and Letters Faculty, 3, 13-25(in Turkish).
[3] Aytaç E., (2011), Fuzzy Logic Approach in Quality Improvement Process, Error Mode and Effects Analysis and Application Example [Master Thesis]. Adnan Menderes University (in Turkish).
[4] Bahrami, M., Bazzaz, D. H., &Sajjadi, S. M. (2012). Innovation AndImprovements In Project Implementation And., (S. 418 – 425). Doi:Https://Doi.Org/10.1016/J.Sbspro.2012.04.050
[5] Chin, K., Wang Y., Poon G., Yang J., (2009) Failure Mode and Effects Analysis By Data Envelopment Analysis, Decision Support Systems48, 246–256
[6] Dagsuyu, C., Göçmen, E., Narlı, M., &Kokangül, A. (2016). Classical And Fuzzy FMEA Risk Analysis İn A Sterilization Unit. Computers &Industrial Engineering, 101, S. 286-294. Doi: Http: // Dx. Doi. Org/ 10. 1016/ J. Cie. 2016. 09.015
[7] Dolaş, K. (2016). Risk Assessment with Fuzzy Logic Method: Example of the Printing Industry (Doctoral Dissertation, Ankara Yıldırım Beyazıt University Health Sciences Institute)(in Turkish).
[8] Gemici, F., & Şahin, A. Ş. (2021) Estimation Of Wind Speed With Artificial Neural Networks Method For Isparta Using Meteorological Measurement Data. International Journal of Energy Applications And Technologies, 8(2), 65-69.
[9] Ivancan, J., &Lisjak, D. (2021). New FMEA Risks Ranking Approach Utilizing Four Fuzzy. Machines, 9, S. 292. Doi:Https://Doi.Org/10.3390/Machines9110292
[10] Karatepe M. (2019), An Intuitionistic Fuzzy Rule-based Approach to FMEA, [Master Thesis].İstanbul Technical University.
[11] Kara-Zaitri C, Fleming PV (1997) Application of Fuzzy İnference Methods To Failure Modeseffects And Criticality Analysis (FMECA). In: International Conference On Safety And Reliability,Pp 2403–241
[12] Korucu, A., Tuğrul A. (2007), Designing a Turkish Visual Interface for Fuzzy Logic Problems [Master Thesis]. Selcuk University (in Turkish).
[13] Özçalık, H. R., Türk, A., C. Y., & Koca, Z. (2008, 11 1). Control of Combustion Fan in Solid Fuel Steam Boiler with Fuzzy Logic Controller. KSU Journal of Science and Engineering, P. 52-58(in Turkish).
[14] Özdemir, O., & Kalınkara, Y. (2020). Fuzzy Logic: A Content Analysis of Thesis and Article Studies Between 2000-2020. Acta Infologica, 4(2), 155-174(in Turkish).
[15] Şimşek, B., & ̇İç, Y. T. (2020). Fuzzy Failure Mode and Effect Analysis Application To Reduce Risk Level. Mathematics And Computers İn Simulation, 178, S. 549–587.
[16] Tay, K. M., &Lim, C. P. (2006). Fuzzy FMEA with A Guided Rules Reduction System for Prioritization of Failures. International Journal of Quality &Reliability Management.
[17] Turan M. (2018). Application of Risk Analysis with Fuzzy FMEA in a Transformer Manufacturer [Master's Thesis]. Balikesir University (in Turkish).
[18] Wang, H., Yi-Minzhang, & Zhouyangc. (2019). A Risk Evaluation Method To Prioritize Failure Modes Based On Failure Data And A Combination Of Fuzzy Sets Theory And Grey Theory. Engineering Applications of Artificial Intelligence, 82, S. 216-225. Doi:Https://Doi.Org/10.1016/J.Engappai.2019.03.023
[19] Wang, Y.-M., Chin, K.-S., Poon, G. K., &Yang, J.-B. (2009). Risk Evaluation İn Failure Mode and Effects Analysis Using Fuzzy. Expert Systems With Applications, 36, S. 1195–1207.
[20] Yel, İ. (2009). Application of Fuzzy Logic Decision Process in Logistics Sector [Master's Thesis]. Yildiz Technical University (in Turkish)
[21] Yörükoğlu H., (2014), Analysis of Renewable Energy Resources Risks by Fuzzy-Fmea Method [Master Thesis]. University of Kocaeli (in Turkish).

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