0d112852-1001-4142-8547-63f42ad3249220210827084342798naun:naunmdt@crossref.orgMDT DepositInternational Journal of Mechanics1998-444810.46300/9104http://www.naun.org/cms.action?id=2828128202112820211510.46300/9104.2021.15https://www.naun.org/cms.action?id=23280Nguyen LamKhanhUniversity of Transport and Communications, Hanoi, VietnamNguyen VanCuongUniversity of Transport and Communications, Hanoi, VietnamMilling is a commonly used method in mechanical machining. This is considered to be the method for the highest productivity among cutting methods. Moreover, the quality of the machined surface is increasingly improved as well as the machining productivity is increasingly enhanced thanks to the development of machine tool and cutting tool manufacturing technology. Therefore, in each specific processing condition (about machine, tool and part material, and other conditions), specific studies are required to determine the value of technological parameters in order to improve productivity and machining accuracy. Only in this way can we take full advantage of the capabilities of modern equipment. The process parameters in the milling method in particular and in the machining and cutting methods in general can be easily adjusted by the machine operator as the parameters of the cutting parameters or the change of tool types. In this article, the combination of Taguchi and Proximity Indexed Value (PIV) methods is presented for multi-criteria decision making in milling. An experimental matrix was designed according to Taguchi method with five input parameters, including the insert materials (TiN, TiCN, and TiAlN), nose radius, cutting velocity, feed rate and depth of cut. The total number of experiments that were performed was twenty-seven. The workpiece used during the experiment was SCM440 steel. At each experiment, the surface roughness was measured and the Material Removal Rate (MRR) was calculated. The weights of these two parameters have been chosen by the decision maker on the basis of consultation with experts. The PIV method was applied to determine the experiment at which the minimum surface roughness and the maximum MRR were simultaneously guaranteed. In addition, the influence of input parameters on surface roughness was also found in this study.8272021827202112713514https://www.naun.org/main/NAUN/mechanics/2021/a282003-014(2021).pdf10.46300/9104.2021.15.14https://www.naun.org/main/NAUN/mechanics/2021/a282003-014(2021).pdf10.24874/ti.969.09.20.11D. D. Trung, Influence of Cutting Parameters on Surface Roughness during Milling AISI 1045 Steel, Tribology in Industry, Vol. 42, No. 4, pp. 658-665, 2020, https://doi.org/10.24874/ti.969.09.20.11 10.37394/23203.2020.15.31K. Dudzik, The possibility of applying acoustic emission method to optimize determination of milling parameters, WSEAS transactions on Systems and Control, Vol. 15, pp. 302-310, 2020, https://doi.org/10.37394/23203.2020.15.31 10.1016/0305-0548(93)90109-vC. –L. Hwang, Y. –J. Lai, Ting_Yun Liu, A new approach for multiple objective decision making. Computers & Operations Research, Vol. 20, No. 8, pp. 889–899, 1993, https://doi.org/10.1016/0305-0548(93)90109-V 10.1016/s0377-2217(03)00020-1S. Opricovic, G. -H. Tzeng, Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research, Vol. 156, No. 2, pp. 445-455, 2004, https://doi.org/10.1016/S0377-2217(03)00020-1 W. Brauers, Optimization methods for a stakeholder society. A revolution in economic thinking by multiobjective optimization, Publisher: springer before Kluwer, https://doi.org/10.1007/978-1-4419-9178-2 10.1007/978-1-4757-3157-6_2Triantaphyllou, Evangelos, Multi-criteria Decision Making Methods: A Comparative Study, Springer – Science + Busines media, 2020, https://www.springer.com/gp/book/9780792366072 10.1016/j.ins.2015.12.011E. Cables Perez , M.T. Lamata , J.L. Verdegay, RIMReference Ideal Method in Multicriteria Decision Making, Information Sciences, vol. 337-338, No. 10, pp. 1-10, 2016, https://doi.org/10.1016/j.ins.2015.12.011 10.1016/j.cie.2018.03.045S. Mufazzal, S. M. Muzakkir, A New Multi-Criterion Decision Making (MCDM) Method Based on Proximity Indexed Value for Minimizing Rank Reversals, Computers & Industrial Engineering, pp.1-38, 2018, https://doi.org/10.1016/j.cie.2018.03.045 V. Gadakh, Application of MOORA method for parametric optimization of milling process, Internationl journal of applied engineering research, Dindigul, Vol. 1, No. 4, pp. 743-758, 2011. S. K. Shihab, A. K. Chanda, Multi Response Optimization Of Milling Process Parameters Using Moora Method, International Journal of Mechanical And Production Engineering, Vol. 3, No. 4, pp. 67-71, 2015. 10.46300/9105.2021.15.1D. D. Trung, Multi-objective optimization of SKD11 steel milling process by Reference Ideal Method, International journal of geology, Vol. 15, pp. 1-16, 2021, https://doi.org/10.46300/9105.2021.15.1 10.1007/s40692-019-00135-7N. Z. Khan, T. S. A.Ansari, A. N. Siddiquee, Z. A. Khan, Selection of E-learning websites using a novel Proximity Indexed Value (PIV) MCDM method, Journal of Computers in Education, Vol. 6, pp. 241-256, 2019, https://doi.org/10.1007/s40692-019-00135-7 10.1177/1464420720966347S. Wakeel, S. Bingol, M. N. Bashir, S. Ahmad, Selection of sustainable material for the manufacturing of complex automotive products using a new hybrid Goal Programming Model for Best Worst Method–Proximity Indexed Value method, Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, Vol. 0, No. 0, pp. 1-15, 2020, https://doi.org/10.1177/1464420720966347 10.18559/ebr.2019.4.3A. Ulutaş, Ç. Karakoy, An analysis of the logistics performance index of EU countries with an integrated MCDM model , Economics and Business Review, Vol. 5 (19), No. 4, pp, 49-69, 2019, https://doi.org/10.18559/ebr.2019.4.3 10.1007/s12046-020-01338-wJ. Raigar, V. S. Sharma, S. Srivastava, R. Chand, J.Singh, A decision support system for the selection of an additive manufacturing process using a new hybrid MCDM technique, Sādhanā, Vol. 45, No. 101, pp. 1-14, 2020, https://doi.org/10.1007/s12046-020-01338-w http://daunhonchinhhang.vn/product/dau-cat-got-phanuoc-tectyl-cool-240/ (at July 20. 2021)