Burak Efe, Mustafa Kurt, Ömer Faruk Efe
1.080 254


This paper aims to establish an occupational health and safety policy for three firms. This paper provides to overcome the drawbacks of traditional FMEA (failure mode and effects analysis) by using an integrated intuitionistic fuzzy multi-criteria decision making method and a linear programming. Priority value of criteria has been defined by utilizing intuitionistic fuzzy analytic hierarchy process method and the highest risky failure mode among failure modes has been found by utilizing intuitionistic fuzzy VIKOR (VIsekriterijumska optimizacija i KOm-promisno Resenje). The application of risk evaluation is conducted to show the effectiveness of the proposed method in three firms. The reliability of the risk ranking is verified by helping of a sensitivity analysis and the advantages of the proposed approach are shown by comparing with the other methods. The managers of the firm present some limitations for the occupational health and safety policy so that these constraints are solved by helping of a linear programming. The results show that destroying of the existing steel ropes during production of plaster, risks that caused from work equipment and electric shock during cutting were determined the highest risky failure modes for construction, textile and metal firms, respectively.


Risk evaluation, intuitionistic fuzzy multi-criteria group decision making, intuitionistic fuzzy set, mathematical programming, FMEA

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Ahmadi, M., Behzadian, K., Ardeshir, A., Kapelan, Z. (2017). Comprehensive risk management using fuzzy FMEA and MCDA techniques in highway construction projects. Journal of Civil Engineering and Management, 23 (2), 300-310.

Arpacioǧlu, Ü., Ersoy, H.Y. (2013). Daylight and energy oriented architecture design support mode, Gazi University Journal of Science, 26 (2), 331-346.

Atanassov, K.T. (1986). Intuitionistic fuzzy sets, Fuzzy Sets and Systems, 20, 87–96.

Boran, F. E., Genç, S., Kurt, M., Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363-11368.

Bowles, J.B., Peláez, C.E. (1995). Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliability Engineering & System Safety, 50(2), 203–213.

Ceylan, H. (2012). Analysis of occupational accidents according to the sectors in Turkey. Gazi University Journal of Science, 25(4), 909-918.

Chang, C. L., Liu, P. H., Wei, C. C. (2001). Failure mode and effects analysis using grey theory. Integrated Manufacturing Systems, 12, 211–216.

Chang, C. L., Wei, C. C., Lee, Y. H. (1999). Failure mode and effects analysis using fuzzy method and grey theory. Kybernetes, 28, 1072–1080.

Chang K.H., Cheng C.H. (2010). A risk assessment methodology using intuitionistic fuzzy set in FMEA. International Journal of Systems Science, 41(12), 1457-1471.

Chatterjee, K., Kar, M. B., Kar, S. (2013). Strategic Decisions Using Intuitionistic Fuzzy Vikor Method for Information System (IS) Outsourcing. 2013 International Symposium on Computational and Business Intelligence, 123-126.

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 & Operations Research, 36, 1768–1779.

Efe, B., Boran, F.E., Kurt, M. (2015). Sezgisel Bulanik Topsis Yöntemi Kullanilarak Ergonomik Ürün Konsept Seçimi. SDÜ Mühendislik Bilimleri ve Tasarım Dergisi, 3(3), 433-440.

Efe, B., Yerlikaya, M.A., Efe, Ö.F. (2016). İş Güvenliğinde Bulanık Promethee Yöntemiyle Hata Türleri ve Etkilerinin Analizi: Bir İnşaat Firmasında Uygulama. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 6(2), 126-137.

Ekmekçioǧlu, M., Kutlu, A.C. (2012). A Fuzzy Hybrid Approach for Fuzzy Process FMEA: An Application to a Spindle Manufacturing Process, International Journal of Computational Intelligence Systems, 5(4), 611-626.

Liu, H.C., Liu, L., Bian, Q.H., Lin, Q.L., Dong, N., Xu, P.C. (2011). Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory. Expert Systems with Applications, 38(4), 4403-4415.

Liu H.C., Liu L., Li P. (2014). Failure mode and effects analysis using intuitionistic fuzzy hybrid weighted Euclidean distance operator. International Journal of Systems Science, 45(10), 2012-2030.

Liu, H.C., Liu, L., Liu, N. (2013). Risk evaluation approaches in failure mode and effects analysis: A literature review. Expert Systems with Applications, 40, 828–838.

Liu, H.C., Liu, L., Liu, N., Mao, L.X. (2012). Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Systems with Applications, 39(17), 12926-12934.

Liu H.C., You J.X., Shan M.M., Shao L.N. (2015a). Failure mode and effects analysis using intuitionistic fuzzy hybrid TOPSIS approach. Soft Computing, 19(4), 1085-1098.

Liu H.C., You J.X., You X.Y., Shan M.M. (2015b). A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method. Applied Soft Computing, 28, 579–588.

Mentes, A., Ozen, E. (2015). A hybrid risk analysis method for a yacht fuel system safety. Safety Science, 79, 94-104.

Mohsen, O., Fereshteh, N. (2017). An extended VIKOR method based on entropy measure for the failure modes risk assessment – A case study of the geothermal power plant (GPP). Safety Science, 92, 160-172.

Opricovic, S., Multi-criteria optimization of civil engineering systems. Belgrade: Faculty of Civil Engineering, 1998.

Opricovic, S., Tzeng, G.H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455.

Opricovic, S., Tzeng, G.H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178(2) 514-529.

Saaty, T.L., The analytic hierarchy process. New York: McGraw-Hill, 1980.

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), 324–336.

Seyed-Hosseini, S.M., Safaei, N., Asgharpour, M.J. (2006). Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique. Reliability Engineering and System Safety, 91(8), 872-881.

Şeker, A. (2014). Using outputs of NASA-TLX for building a mental workload expert system. Gazi University Journal of Science, 27 (4), 1132-1142.

Tooranloo, H. S., Sadat Ayatollah, A. (2016). A model for failure mode and effects analysis based on intuitionistic fuzzy approach. Applied Soft Computing, 49, 238-247.

Vahdani B., Salimi M., Charkhchian M. (2015). A new FMEA method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process. The International Journal of Advanced Manufacturing Technology, 77(1-4) 357–368.

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 & Industrial Engineering, 102, 175-185.

Xu, Z. (2007). Intuitionistic fuzzy aggregation operators. IEEE Transaction of Fuzzy Systems, 15(6), 1179–1187.

Xu, Z., Liao, H. (2014). Intuitionistic fuzzy analytic hierarchy process. IEEE Transactions on Fuzzy Systems, 22 (4), 749-761.

Xu, Z., Yager, R.R. (2006). Some geometric aggregation operators based on intuitionistic fuzzy sets. International Journal of General System, 35, 417–433.