Multi-Objective Optimization of Turning Process by Fuca Method

[1] El-Axir, M. H., Elkhabeery, M. M., Okasha, M. M. “Modeling and Parameter Optimization for Surface Roughness and Residual Stress in Dry Turning Process”, Engineering, Technology & Applied Science Research 7(5), pp. 2047 – 2055 , 2017. DOI: 10.48084/etasr.1560Search in Google Scholar

[2] Dasari, K. R., Kolla, S. “Comparision of dominant features identification for tool wear in hard turning of INCONEL 718 by using vibration analysis”, Strojnícky časopis – Journal of Mechanical Engineering 69(4), pp. 1 - 8, 2019. DOI: 10.2478/scjme-2019-0038Search in Google Scholar

[3] Trung, D. D., Nguyen, N. T., Duc, D. V. “Study on multi-objective optimization of the turning process of EN 10503 steel by combination of Taguchi method and Moora technique”, EUREKA: Physics and Engineering 2021(2), pp. 52 – 65, 2021. DOI: 10.21303/2461-4262.2020.001414Search in Google Scholar

[4] Reddy, N. M. M., Chaganti, P. K. “Investigating Optimum SiO2 Nanolubrication During Turning of AISI 420 SS”, Engineering, Technology & Applied Science Research 9(1), pp. 3822 – 3825, 2019. DOI: 10.48084/etasr.2537Search in Google Scholar

[5] Divya, Ch., Suvarna Raju, L., Singaravel, B. “Application of MCDM Methods for Process Parameter Optimization in Turning Process-A Review”, Recent Trends in Mechanical Engineering, 2020, pp. 199 – 207, 2020. DOI: 10.1007/978-981-15-7557-0_18Search in Google Scholar

[6] Chakraborty, S., Jana, T. K., Paul, S. “On the application of multi criteria decision making technique for multi-response optimization of metal cutting process”, Intelligent Decision Technologies, 13(1), pp. 101 – 115, 2019. DOI: 10.3233/IDT-190356Search in Google Scholar

[7] Reda, M. S. A., Omer, A. B. “Two New Approaches (RAMS-RATMI) in Multi-Criteria Decision-Making Tactics”, Journal of Mathematics 2022, 6725318, 2020. DOI: 10.1155/2022/6725318Search in Google Scholar

[8] Anup, A. J., Jay, C. G., Akanksha. K. B., Shraddha. K. W., Yashwant. H., Nehal. K. “Parametric optimization of bearing steel turning process using MCDM hybrid technique”, International journal of innovative research in technology 9 (2), pp. 333 – 340, 2022.Search in Google Scholar

[9] Suresh, R. K., Krishnaiah, G., Venkataramaiah, P. “Selection of best novel MCDM method during turning of hardened AISI D3 tool steel under minimum quantity lubrication using Bio-degradable oils as cutting fluids”, International Journal of Applied Engineering Research 12 (19), pp. 8082 – 8091, 2017.Search in Google Scholar

[10] Singaravel, B., PrabhuShankar, D. “Application of MCDM Method for the Selection of Optimum Process Parameters in Turning Process”, Materialstoday: proceedings 5 (5), pp. 13464 – 13471, 2018. DOI: 10.1016/j.matpr.2018.02.341Search in Google Scholar

[11] Saha, A., Majumder, H. “Multi Criteria Selection of Optimal Machining Parameter in Turning Operation Using Comprehensive Grey Complex Proportional Assessment Method for ASTM A36”, International Journal of Engineering Research in Africa 23, pp. 24 – 32, 2016. DOI: 10.4028/www.scientific.net/JERA.23.24Search in Google Scholar

[12] Sharma, V. “Multi-Objective Optimization in Hard Turning of Tool Steel Using Integration of Taguchi & TOPSIS under wet Conditions”, International Journal of Engineering Trends and Technology 68(10), pp. 37 – 41, 2020. DOI: 10.14445/22315381/IJETT-V68I10P206Search in Google Scholar

[13] Bhanu Prakash, D., Krishnaiah, Dr. G, Shankar, N. V. S. “Optimization of process parameters using AHP and TOPSIS when turning AISI 1040 steel with coated tools”, International Journal of Mechanical Engineering and Technology 7(6), pp. 483 – 492, 2016.Search in Google Scholar

[14] Singaravel, B., Selvaraj, T. “Optimization of machining parameters in turning operation using combined TOPSIS and AHP method”, Tehnički vjesnik 22 (6), pp. 1475 – 1480, 2015. DOI: 10.17559/TV-20140530140610Search in Google Scholar

[15] Reddy, V. V. “Turning process parameters optimization of AL7075 hybrid mmc’s composite using topsis method”, Journal of engineering and Natural sciences 38 (4), pp. 2043 – 2055, 2021.Search in Google Scholar

[16] Maity, K., Khan, A. “Application of MCDM-based TOPSIS method for the selection of Optimal Process Parameter in Turning of Pure Titanium”, Benchmarking: An International Journal, 2017. DOI: 10.1108/BIJ-01-2016-0004Search in Google Scholar

[17] Trung, D. D. “Application of TOPSIS and PIV methods for multi-criteria decision making in hard turning process”, Journal of Machine Engineering 21 (4), pp. 57 – 71, 2021. DOI: 10.36897/jme/142599Search in Google Scholar

[18] Majumder, H., Saha, A. “Application of MCDM based hybrid optimization tool during turning of ASTM A588”, Decision Science Letters 7, pp. 143 – 156, 2018. DOI: 10.5267/j.dsl.2017.6.003Search in Google Scholar

[19] Sivalingam, V., Poogavanam, G., Natarajan, Y., Sun, J. “Optimization of Atomized Spray Cutting Fluid EcoFriendly Turning of Inconel 718 Alloy Using ARAS and CODAS Methods”, Research Square, 2021. DOI: 10.21203/rs.3.rs-988214/v1Search in Google Scholar

[20] Dubey, V., Sharma, A. K., Vats, P., Pimenov, D. Y., Giasin, K., Chuchala, D. “Study of a Multicriterion Decision-Making Approach to the MQL Turning of AISI 304 Steel Using Hybrid Nanocutting Fluid”, Materials (Basel) 14 (23), 7207, 2021. DOI: 10.3390/ma14237207Search in Google Scholar

[21] Trung, D. D., Tung, N. N. “Applying COCOSO, MABAC, MAIRCA, EAMR, TOPSIS and weight determination methods for multi-criteria decision making in hole turning process”, Strojnícky časopis – Journal of Mechanical Engineering 72 (2), pp. 15 – 40, 2022. DOI: 10.2478/scjme-2022-0014Search in Google Scholar

[22] Trung, D. D. “Comparison R and CURLI methods for multi-criteria decision making”, Advanced Engineering Letters 1(2), pp. 46 – 56, 2022. DOI: 10.46793/adeletters.2022.1.2.3Search in Google Scholar

[23] Trung, D. D. “A combination method for multi-criteria decision making problem in turning process”, Manufacturing review 8 (26), 2021. DOI: 10.1051/mfreview/2021024Search in Google Scholar

[24] Fernando, M. M. L, Escobedo, J. L. P., Azzaro-Pantel, C., Pibouleau, L., Domenech, S., Aguilar-Lasserre, A. “Selecting the best alternative based on a hybrid multiobjective GA-MCDM approach for new product development in the pharmaceutical industry”, IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM), 2021. DOI: 10.1109/SMDCM.2011.5949271Search in Google Scholar

[25] Trung, D. D. “Application of FUCA method for multi-criteria decision making in mechanical machining processes”, Operational Research in Engineering Sciences: Theory and Applications 5 (3), pp. 131 – 152, 2022. DOI: 10.31181/oresta051022061dSearch in Google Scholar

[26] Baydas, M. “The effect of pandemic conditions on financial success rankings of BIST SME industrial companies: a different evaluation with the help of comparison of special capabilities of MOORA, MABAC and FUCA methods”, Business & Management Studies: An International Journal 10 (1), pp. 245 – 260, 2022.Search in Google Scholar

[27] Baydas, M. “Comparison of the Performances of MCDM Methods under Uncertainty: An Analysis on Bist SME Industry Index”, OPUS – Journal of Society Research 19 (46), pp. 308 – 326, 2022.Search in Google Scholar

[28] Baydas, M., Pamucar, D. “Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data”, Mathematics 10(7), pp. 1 – 25, 2022.Search in Google Scholar

[29] Baydas, M., Elma, O. E., Pamucar, D. “Exploring the specific capacity of different multi criteria decision making approaches under uncertainty using data from financial markets”, Expert Systems with Applications 197, 2022. DOI: 10.1016/j.eswa.2022.116755Search in Google Scholar

[30] Ouattara, A., Pibouleau, L., Azzaro-Pantel, C., Domenech, S., Baudet, P., Benjamin, Y. “Economic and environmental strategies for process design”, Computers & Chemical Engineering 36 (10), pp. 174 – 188, 2012.Search in Google Scholar

[31] Zavadskas, E. K., Antucheviciene, J., Chatterjee, P. “Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management”, Information, 2019. DOI: 10.3390/books978-3-03897-643-1Search in Google Scholar

[32] Trung, D. D., Thinh, H. X. “A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study”, Advances in Production Engineering & Management 16 (4), pp. 443 – 456, 2021. DOI: 10.14743/apem2021.4.412Search in Google Scholar

[33] Dawes, R. M., Coorigan, B. “Linear Models in Decision Malking”, Psychological Bulletin 81, pp. 95 – 106, 1974.Search in Google Scholar

[34] Einhorn H. J., Mccoach W. “A Symble Multiattribute Utility Procedure for Evaluation”, Behavioral Scicence 22 (4), pp. 270 – 282, 1997.Search in Google Scholar

[35] Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. “Determination of objective weights using a new method based on the removal effects of criteria (MEREC)”, Symmetry 13 (4), pp. 1 – 20, 2021.Search in Google Scholar

[36] Trung, D. D., Thinh, H. X., Ha, L. D. “Comparison of the RAFSI and PIV method in multi-criteria decision making: application to turning processes”, International Journal of Metrology and Quality Engineering 13 (14), 2022. DOI: 10.1051/ijmqe/2022014Search in Google Scholar

[37] Tien, D. H., Trung, D. D., Thien, N. V., Nguyen, N. T. “Multi-objective optimization of the cylindrical grinding process of SCM440 steel using preference selection index method”, Journal of Machine Engineering 21 (3), pp. 110 – 123, 2021. DOI: 10.36897/jme/141607Search in Google Scholar

[38] Nguyen, N. T., Trung, D. D. “Combination of Taguchi method, Moora and Copras techniques in multi-objective optimization of surface grinding process”, Journal of Applied Engineering Science 19(2), pp. 390 – 398, 2021. DOI: 10.5937/jaes0-28702Search in Google Scholar

[39] Thien, N. V., Tien, D. H., Trung, D. D., Nguyen, N. T. “Multi-Objective Optimization of turning process using VIKOR method”, Journal of Applied Engineering Science 19 (4), pp. 868 – 873, 2021. DOI: 10.5937/jaes0-29654Search in Google Scholar