A STRUCTURED FRAMEWORK FOR RELIABILITY AND RISK EVALUATION IN THE MILK PROCESS INDUSTRY UNDER FUZZY ENVIRONMENT
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García-Burgos, M., Moreno-Fernández, J., Alférez, M. J., Díaz-Castro, J., López-Aliaga, I., 2020, New perspectives in fermented dairy products and their health relevance, Journal of Functional Foods, 72, pp. 104059.
Wang, L., Chu, J., Wu, J., 2007, Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process, International journal of production economics, 107(1), pp. 151-163.
Aggarwal, A.K., Kumar, S., Singh, V., 2016, Reliability and availability analysis of the serial processes in skim milk powder system of a dairy plant: a case study, International Journal of Industrial and Systems Engineering, 22(1), pp. 36-62.
Gowid, S., Dixon, R., Ghani, S., 2014, Optimization of reliability and maintenance of liquefaction system on FLNG terminals using Markov modelling, International Journal of Quality & Reliability Management, 31(3), pp. 293-310.
Knezevic, J., Odoom, E.R., 2001, Reliability modeling of repairable systems using Petri nets and fuzzy Lambda–Tau methodology, Reliability Engineering & System Safety, 73(1), pp. 1-17.
Gupta, P., Lal, A.K., Sharma, R.K., Singh, J., 2005, Numerical analysis of reliability and availability of the serial processes in butter-oil processing plant, International Journal of Quality & Reliability Management, 22(3), pp. 303-316.
Aksu, S., Aksu, S., Turan, O., 2006, Reliability and availability of pod propulsion systems, Quality and Reliability Engineering International, 22(1), pp. 41-58.
Qiu, Z., Yang, D., Elishakoff, I., 2008, Probabilistic interval reliability of structural systems, International Journal of Solids and Structures, 45(10), pp. 2850-2860.
Sharma, R.K., Kumar, D., Kumar, P., 2008, Predicting uncertain behavior of industrial system using FM—A practical case, Applied Soft Computing, 8(1), pp. 96-109.
Sharma, S.P., Kumar, D., 2010, RAM analysis of repairable industrial systems utilizing uncertain data. Applied Soft Computing, 10(4), pp. 1208-1221.
Zhang, S.F., Liu, S.Y., Zhai, R.H., 2011, An extended GRA method for MCDM with interval-valued triangular fuzzy assessments and unknown weights, Computers & Industrial Engineering, 61(4), pp. 1336-1341.
Durmić, E., Stević, Ž., Chatterjee, P., Vasiljević, M., Tomašević, M., 2020, Sustainable supplier selection using combined FUCOM–Rough SAW model, Reports in Mechanical Engineering, 1(1), pp. 34-43.
Bozanic, D., Tešić, D., Milić, A., 2020, Multicriteria decision making model with Z-numbers based on FUCOM and MABAC model, Decision Making: Applications in Management and Engineering, 3(2), pp. 19-36.
Badi, I., Pamucar, D., 2020, Supplier selection for steelmaking company by using combined Grey-MARCOS methods, Decision Making: Applications in Management and Engineering, 3(2), pp. 37-48.
Kishore, R., Dehmourdi, S.A.M., Naik, M.G., Hassanpour, M., 2020, Designing a framework for Subcontractor’s selection in construction projects using MCDM model, Operational Research in Engineering Sciences: Theory and Applications, 3(3), pp. 48-64.
Vesković, S., Milinković, S., Abramović, B., Ljubaj, I., 2020, Determining criteria significance in selecting reach stackers by applying the fuzzy PIPRECIA method, Operational Research in Engineering Sciences: Theory and Applications, 3(1), pp. 72-88.
Chatterjee, P., Chakraborty, S., 2017, Development of a meta-model for the determination of technological value of cotton fiber using design of experiments and the TOPSIS method, Journal of Natural Fibers, 18(6), pp. 882-895.
Maity, S.R., Chatterjee, P., Chakraborty, S., 2012, Cutting tool material selection using grey complex proportional assessment method, Materials & Design (1980-2015), 36, pp. 372-378.
Sharma, S.P., Kumar, D., Kumar, A., 2012, Behavior prediction of washing system in a paper industry using GA and fuzzy lambda–tau technique, Applied Mathematical Modeling, 36 (6), pp. 2614-2626.
Deveci, H.C., Esen, H., Hatipoğlu, T., Fığlalı, N., 2014, Implementation of reliability-centred FMEA in a cable cutting process, International Journal of Quality Engineering and Technology, 4(4), pp. 334-351.
Garg, H., Rani, M., Sharma, S.P., 2014, An approach for analyzing the reliability of industrial systems using soft-computing based technique, Expert systems with Applications, 41(2), pp. 489-501.
Panchal, D., Kumar, D., 2014, Reliability analysis of CHU system of coal fired thermal power plant using fuzzy λ-τ approach. Procedia Engineering, 97, pp. 2323-2332.
Panchal, D., Singh, A.K., Chatterjee, P., Zavadskas, E.K., Keshavarz-Ghorabaee, M., 2019, A new fuzzy methodology-based structured framework for RAM and risk analysis, Applied Soft Computing, 74, pp. 242-254.
Zavadskas, E.K., Antucheviciene, J., 2007, Multiple criteria evaluations of rural building's regeneration alternatives, Building and Environment, 42(1), pp. 436-451.
Panchal, D., Kumar, D., 2016, Integrated framework for behaviour analysis in a process plant, Journal of loss prevention in the process industries, 40, pp. 147-161.
Babashamsi, P., Golzadfar, A., Yusoff, N.I.M., Ceylan, H., Nor, N.G.M., 2016, Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities, International Journal of Pavement Research and Technology, 9(2), pp. 112-120.
Komal., 2015, Fuzzy fault tree analysis for patient safety risk modeling in healthcare under uncertainty, Applied Soft Computing, 37, pp. 942-951.
Wang, Y.M., Chin, K.S., Poon, G.K.K., Yang, J.B., 2009, Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean, Expert systems with applications, 36(2), pp. 1195-1207.
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), pp. 324-335.
Panchal, D., Jamwal, U., Srivastava, P., Kamboj, K., Sharma, R., 2018, Fuzzy methodology application for failure analysis of transmission system, International Journal of Mathematics in Operational Research, 12(2), pp. 220-237.
Panchal, D., Mangla, S.K., Tyagi, M., Ram, M., 2018, Risk analysis for clean and sustainable production in a urea fertilizer industry, International Journal of Quality & Reliability Management, 35(7), pp. 1459-1476.
Yazdani, M., Alidoosti, A., Zavadskas, E.K., 2011, Risk analysis of critical infrastructures using fuzzy COPRAS, Economic research-Ekonomska istraživanja, 24(4), pp. 27-40.
Turanoglu Bekar, E., Cakmakci, M., Kahraman, C., 2016, Fuzzy COPRAS method for performance measurement in total productive maintenance: a comparative analysis, Journal of Business Economics and Management, 17(5), pp. 663-684.
Dhiman, H.S., Deb, D., 2020, Fuzzy TOPSIS and fuzzy COPRAS based multi-criteria decision making for hybrid wind farms, Energy, 202, pp. 117755.
Mousavi-Nasab, S.H., Sotoudeh-Anvari, A., 2017, A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems, Materials & Design, 121, pp. 237-253.
Alkan, Ö., Albayrak, Ö. K., 2020, Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA, Renewable Energy, 162, pp. 712-726.
Fouladgar, M. M., Yazdani-Chamzini, A., Lashgari, A., Zavadskas, E. K., Turskis, Z., 2012, Maintenance strategy selection using AHP and COPRAS under fuzzy environment, International journal of strategic property management, 16(1), pp. 85-104.
Chatterjee, P., Athawale, V. M., Chakraborty, S., 2011, Materials selection using complex proportional assessment and evaluation of mixed data methods, Materials & Design, 32(2), pp. 851-860.
Kutlu, A.C., Ekmekçioğlu, M., 2012, Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP, Expert Systems with Applications, 39(1), pp. 61-67.
Chan, F. T., Kumar, N., Tiwari, M. K., Lau, H. C., Choy, K., 2008, Global supplier selection: a fuzzy-AHP approach. International Journal of production research, 46(14), pp. 3825-3857.
Nădăban, S., Dzitac, S., Dzitac, I., 2016, Fuzzy topsis: A general view, Procedia Computer Science, 91, pp. 823-831.
Zolfani, S., Yazdani, M., Pamucar, D., Zaraté, P., 2020, A VIKOR and TOPSIS focused reanalysis of the MADM methods based on logarithmic normalization, Facta Universitatis-Series Mechanical Engineering, 18(3), pp. 341-355.
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), pp. 445-455.
Zavadskas, E.K., Turskis, Z., Kildienė, S., 2014, State of art surveys of overviews on MCDM/MADM methods, Technological and economic development of economy, 20(1), pp. 165-179.
Dağdeviren, M., Yavuz, S., Kılınç, N., 2009, Weapon selection using the AHP and TOPSIS methods under fuzzy environment, Expert systems with applications, 36(4), pp. 8143-8151.
Taylan, O., Bafail, A.O., Abdulaal, R.M., Kabli, M.R., 2014, Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies, Applied Soft Computing, 17, pp. 105-116.
Şengül, Ü., Eren, M., Shiraz, S.E., Gezder, V., Şengül, A.B., 2015, Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey, Renewable energy, 75, pp. 617-625.
Stević, Ž., Tanackov, I., Vasiljević, M., Novarlić, B., Stojić, G., 2016, An integrated fuzzy AHP and TOPSIS model for supplier evaluation, Serbian Journal of Management, 11(1), pp. 15-27.
Chatterjee, P., Stević, Ž., 2019, A two-phase fuzzy AHP-fuzzy TOPSIS model for supplier evaluation in manufacturing environment, Operational Research in Engineering Sciences: Theory and Applications, 2(1), pp. 72-90.
Kushwaha, D.K., Panchal, D., Sachdeva, A., 2020, Risk analysis of cutting system under intuitionistic fuzzy environment, Reports in Mechanical Engineering, 1(1), pp. 162-173.
DOI: https://doi.org/10.22190/FUME201123004G
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