This is an open access article distributed under the CC BY 4.0
Volume 21 article 1061 pages: 167-175
Selecting the right cutting tool material for the type of workpiece material plays a very important role in the machining process. The efficiency of the machining process is greatly influenced by this selection. The tables in the manuals or the manufacturer's instructions are commonly used documents for the selection of cutting tool materials. Within each of these document types, the cutting tool materials were described by different criteria. So, tool selection is considered as a multi-criteria decision-making activity. The values of the criteria for each type of cutting tool can be a number or a certain range. This study proposes a new method to rank and select cutting tools. First, a ranking of the solutions for each criterion will be performed. This ranking is based on the mean value of the criteria in each solution. Therefore, this method is called “Ranking the Solutions based on the Mean Value of Criteria - RSMVC”. The RSMVC method was proven to be a highly reliable method for ranking the cutting tool materials. These results were successfully verified when solving the problems in different cases of cutter material selection.
1. Zopounidis, C., Doumpos, M. (2017). Multiple Criteria Decision Making - Applications in Management and Engineering. Springer.
2. Trung, D. D. (2022). Expanding Data Normalization Method to CODAS Method for Multi-Criteria Decision Making. Applied Engineering Letters, vol.7, no.2, 54-66, DOI: 10.18485/aeletters.2022.7.2.2
3. Trung, D.D. (2021). A combination method for multi-criteria decision making problem in turning process. Manufacturing review, vol. 8, no. 26, 1-17, DOI: 10.1051/mfreview/2021024
4. Trung, D. D., Nhu-Tung, N. (2022). Applying Cocoso, Mabac, Mairca, Eamr, Topsis and weight determination methods for multi-criteria decision making in hole turning process, Strojnicky casopis – Journal of mechanical engineering, vol. 72, no. 2, 15-40, DOI: 10.2478/scjme-2022-0014
5. Huu-Quang, N., Xuan-Hung, L., Thanh-Tu, N., Quoc-Hoang, T., Ngoc-Pi, V. (2022). A Comparative Study on Multi-Criteria Decision-Making in Dressing Process for Internal Grinding, Machines, vol. 10, no. 5, 1 – 14, DOI: 10.3390/machines10050303
6. Huu-Quang, N., Van-Tung, N., Dang-Phong, P., Quoc-Hoang, T., Ngoc-Pi, V. (2022). Multi-criteria decision making in the PMEDM process by using MARCOS, TOPSIS, and MAIRCA methods, Applied sciences, vol. 12, no. 8, 1 – 11, DOI: 10.3390/app12083720
7. Trung, D. D., Truong, N. X., Thinh, H. X. (2022). Combined Priprecia method and modified Fuca method for selection of lathe, Journal of Applied Engineering Science, vol. 20, no. 4, 1355-1365, DOI: 10.5937/jaes0-39335
8. Stevi, Z., Brkovic, N. (2020). A novel integrated FUCOM-MARCOS model for evaluation of human resources in a transport company, Logistics, vol. 4, no. 4, 1-14, DOI: 10.3390/logistics4010004
9. Guini, F., Barkany, A. E., Jabri, A., Irhirane, E. H. (2018). An Approach for the Evaluation of a Product's Process Planning during the Design Phase through a Group Multi-Criteria Decision-Making, International Journal of Engineering Research in Africa, vol. 38, 154-162, DOI: 10.4028/www.scientific.net/JERA.38.154
10. Tien, D. H., Trung, D. D., Thien, N. V., Nguyen, N. T. (2021). Multi-objective optimization of the cylindrical grinding process of scm440 steel using preference selection index method, Journal of Machine Engineering, vol. 21, no. 3, 110-123, DOI: 10.36897/jme/141607
11. Thien, N. V., Tien, D. H., Nguyen, N. T., Trung, D. D. (2021). Multi-Objective Optimization of turning process using VIKOR method, Journal of Applied Engineering Science, vol. 19. no. 4, 868-873, DOI: 10.5937/ jaes0-29654
12. Youssef, H. A., El-Hofy, H. (2008). Machining Technology- Machine Tools and Operations. CRC Press, DOI: 10.1201/9781420043402
13. Calıskan, H., Kursuncu, B., Kurbanoglu, C., Guven, S.Y. (2013). Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods. Materials and Design, vol. 45, 473–479, DOI: 10.1016/j.matdes.2012.09.042
14. Majumder, H., Saha, A. (2018). Application of MCDM based hybrid optimization tool during turning of ASTM A588. Decision Science Letters, vol. 7, 153-156, DOI: 10.5267/j.dsl.2017.6.003
15. Niu, J., Huang, C., Li, C., Zou, B., Xu, L., Wang, J., Liu, Z. (2020). A comprehensive method for selecting cutting tool materials. The International Journal of Advanced Manufacturing Technology, vol. 110, 229–240, DOI: 10.1007/s00170-020-05534-0
16. Dich, T.V., Binh, N.T., Dat, N.T., Tiep, N.V., Viet, T.X. (2003). Manufacturing Technology. Science and Technics Publishing House, Hanoi.
17. Sandvik Coromant. Available at: https://www.sandvik.coromant.com/en-gb/pages/default.aspx (access: November 16, 2022).
18. Milos, M., Miroslav, R., Dusan, P., Bogdan, N. (2015). Selection Of Cutting Inserts For Aluminum Alloys Machining By Using MCDM Method. Acta Universitatis Cibiniensis. Technical Series, vol. 66, 98-101, DOI: 10.1515/aucts-2015-0035
19. Shelar, P. R., Lekurwale, R. R. (2016). Selecting Appropriate Cutting Tool Insert For Turning Using Analytical Hierarchy Process And Weighted Product Method. International Journal of Mechanical and Production Engineering, vol. 4, no. 5, 1-4.
20. Singaravel, B., Shankar, D. P., Prasanna, L. (2018). Application of MCDM Method for the Selection of Optimum Process Parameters in Turning Process. Materials Today: Proceedings, vol. 5, 13464–13471, DOI: 10.1016/j.matpr.2018.02.341
21. Maity, S. R., Chatterjee, P., Chakraborty, S. (2012). Cutting tool material selection using grey complex proportional assessment method. Materials and Design, vol. 36, 372–378, DOI: 10.1016/j.matdes.2011.11.044
22. Suresh, R. K., Krishnaiah, G., Venkataramaiah, P. (2017). 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, vol. 12, no. 19, 8082-8091.
23. Nikam, K. G., Kadam, S. S. (2014). Selection of Cutting Tool Insert in Turning of EN 8 Steel using Multiple Attribute Decision Making (MADM) Methods. International Journal of Engineering Sciences & Research Technology, vol 3, no. 12, 109-115.
24. Jahan, A., Yazdani, M., Edwards, K. L. (2021). TOPSIS-RTCID for range target-based criteria and interval data. International Journal of Production Management and Engineering, vol.9, no. 1, 1-14.
25. Rao, R. V., Lakshmi, J. (2021). R-method: A simple ranking method for multi-attribute decision-making in the industrial environment. Journal of Project Management, vol. 6, 223–230, DOI: 10.5267/j.jpm.2021.5.001
26. Trung, D. D. (2022). Comparison R and CURLI methods for multi-criteria decision making. Advanced Engineering Letters, vol. 1, no. 2, 46-56, DOI: 10.46793/adeletters.2022.1.2.3
27. Fernando, M.M.L., Escobedo, J.L.P., Azzaro-Pantel, C., Pibouleau, L., Domenech, S., Aguilar-Lasserre, A. (2021). 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), https://ieeexplore.ieee.org/document/5949271
28. Bozanic, D., Milic, A., Tesic, D., Sałabun, W., Pamucar, D. (2021). D numbers – fucom – fuzzy rafsi model for selecting the group of construction machines for enabling mobility. Facta Universitatis Series Mechanical Engineering, vol. 19, no. 3, 447-471, DOI: 10.22190/FUME210318047B
29. Muhammad, L. J., Badi, I., Haruna, A. A., Mohammed, I. A. (2021). Selecting the Best Municipal Solid Waste Management Techniques in Nigeria Using Multi Criteria Decision Making Techniques. Reports in Mechanical Engineering, vol. 2, no. 1, 2021, 180-189, DOI: 10.31181/rme2001021801b
30. Pamucar, D., Bozanic, D., Randelovic, A. (2017). Multi-criteria decision making: An example of sensitivity analysis. Serbian Journal of Management, vol. 12, no. 1, 1-27, DOI: 10.5937/sjm12-9464
31. Li, A., Zhao, J., Gong, Z., Lin, F. (2016). Optimal selection of cutting tool materials based on multi-criteria decision-making methods in machining Al-Si piston alloy. The International Journal of Advanced Manufacturing Technology, vol. 86, 1055-1062, DOI: 10.1007/s00170-015-8200-1
32. Calıskan, H. (2013). Selection of boron based tribological hard coatings using multi-criteria decision making methods. Materials and Design, vol. 50, DOI: 10.1016/j.matdes.2013.03.059