A research on application of the measurement of alternatives and ranking according to compromise solution method for multi-criteria decision making in the grinding process

Keywords: MCDM, MARCOS, Entropy, Grinding, Surface roughness, Vibration, Material removal yield


The efficiency of cutting methods in general and the grinding method in particular is evaluated through many parameters such as surface roughness, machining productivity, system vibrations, etc. The machining process is considered highly efficient when it meets the set requirements for these parameters such as ensuring the small surface roughness, small vibrations, and high productivity, etc. However, for each specific machining condition, sometimes the set criteria for the output criteria are opposite. In these cases, it is required to solve the Multi-Criteria Decision Making (MCDM) which means making the decision to ensure the harmonization of all criteria. In this study, a study on multi-criteria decision making in the grinding process of 9CrSi steel using CBN grinding wheels is presented. The experimental process was carried out with sixteen experiments according to an orthogonal matrix that designed by the Taguchi method. The workpiece velocity, feed rate, and depth of cut were changed in each experiment. At each experiment, the responses were determined including surface roughness (Ra), the vibration of the grinding wheel shaft in the three directions, corresponding to Ax, Ay, and Az, and material removal yield (Q). Four determination methods of weights for criteria were used. The Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method was applied for multi-criteria decision making. The objective of this study is to identify an experiment that simultaneously ensures the small values of Ra, Ax, Ay, and Az and large value Q


Download data is not yet available.

Author Biographies

Hoang Xuan Thinh, Hanoi University of Industry

Center for Mechanical Engineering

Do Duc Trung, Hanoi University of Industry

Faculty of Mechanical Engineering


Tung, L. A., Pi, V. N., Ha, D. T. T., Hung, L. X., Banh, T. L. (2018). A Study on Optimization of Surface Roughness in Surface Grinding 9CrSi Tool Steel by Using Taguchi Method. Lecture Notes in Networks and Systems, 100–108. doi: https://doi.org/10.1007/978-3-030-04792-4_15

Anh Tung, L., Pi, V. N., Lien, V. T., Thi Hong, T., Hung, L. X., Tien Long, B. (2019). Optimization of dressing parameters of grinding wheel for 9CrSi tool steel using the taguchi method with grey relational analysis. IOP Conference Series: Materials Science and Engineering, 635 (1), 012030. doi: https://doi.org/10.1088/1757-899x/635/1/012030

Xuan Tu, H., Thao, L. P., Thi Hong, T., Thi Thanh Nga, N., Trung, D. D., Gong, J., Pi, V. N. (2019). Influence of dressing parameters on surface roughness of workpiece for grinding hardened 9XC tool steel. IOP Conference Series: Materials Science and Engineering, 542 (1), 012008. doi: https://doi.org/10.1088/1757-899x/542/1/012008

Xuan Hung, L., Ngoc Pi, V., Thi Hong, T., Hong Ky, L., Thi Lien, V., Anh Tung, L., Tien Long, B. (2019). Multi-objective Optimization of Dressing Parameters of Internal Cylindrical Grinding for 9CrSi Aloy Steel Using Taguchi Method and Grey Relational Analysis. Materials Today: Proceedings, 18, 2257–2264. doi: https://doi.org/10.1016/j.matpr.2019.07.007

Hong, T. T., Cuong, N. V., Ky, L. H., Nguyen, Q. T., Long, B. T., Tung, L. A. et. al. (2020). Multi-Criteria Optimization of Dressing Parameters for Surface Grinding 90CrSi Tool Steel Using Taguchi Method and Grey Relational Analysis. Materials Science Forum, 998, 61–68. doi: https://doi.org/10.4028/www.scientific.net/msf.998.61

Sinha, M. K., Setti, D., Ghosh, S., Venkateswara Rao, P. (2016). An investigation on surface burn during grinding of Inconel 718. Journal of Manufacturing Processes, 21, 124–133. doi: https://doi.org/10.1016/j.jmapro.2015.12.004

Shi, Z., Malkin, S. (2005). Wear of Electroplated CBN Grinding Wheels. Journal of Manufacturing Science and Engineering, 128 (1), 110–118. doi: https://doi.org/10.1115/1.2122987

Yu, T. (2016). Material removal modeling and life expectancy of electroplated CBN grinding wheel and paired polishing. Iowa State University. doi: https://doi.org/10.31274/etd-180810-5672

Lee, K. W., Wong, P. K., Zhang, J. H. (2000). Study on the grinding of advanced ceramics with slotted diamond wheels. Journal of Materials Processing Technology, 100 (1-3), 230–235. doi: https://doi.org/10.1016/s0924-0136(00)00403-9

Marinescu, I. D., Hitchiner, M. P., Uhlmann, E., Rowe, W. B., Inasaki, I. (2006). Handbook of Machining with Grinding Wheels. CRC Press, 632. doi: https://doi.org/10.1201/9781420017649

Malkin, S., Guo, C. (2008). Grinding technology: Theory and Applications of Machining with Abrasives. New York: Industrial Press, 372.

Cao, Y., Guan, J., Li, B., Chen, X., Yang, J., Gan, C. (2012). Modeling and simulation of grinding surface topography considering wheel vibration. The International Journal of Advanced Manufacturing Technology, 66 (5-8), 937–945. doi: https://doi.org/10.1007/s00170-012-4378-7

Nguyen, N.-T., Duc Trung, D. (2020). A study on the surface grinding process of the SUJ2 steel using CBN slotted grinding wheel. AIMS Materials Science, 7 (6), 871–886. doi: https://doi.org/10.3934/matersci.2020.6.871

Liu, T., Deng, Z., Lv, L., She, S., Liu, W., Luo, C. (2020). Experimental Analysis of Process Parameter Effects on Vibrations in the High-Speed Grinding of a Camshaft. Strojniški Vestnik – Journal of Mechanical Engineering, 66 (3), 175–183. doi: https://doi.org/10.5545/sv-jme.2019.6294

Nguyen, N.-T., Tien, D. H., Trung, D. D. (2020). Multi-Objective Optimization when Surface Grinding the 3X13 Steel by Combining the General Reduced Gradient Algorithm and Harmonic Mean Method. Advances in Science, Technology and Engineering Systems Journal, 5 (5), 395–400. doi: https://doi.org/10.25046/aj050550

Stević, Ž., Pamučar, D., Puška, A., Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140, 106231. doi: https://doi.org/10.1016/j.cie.2019.106231

Tadić, S., Kilibarda, M., Kovač, M., Zečević, S. (2021). The assessment of intermodal transport in countries of the danube region. International Journal for Traffic and Transport Engineering, 11 (3), 375–391. doi: https://doi.org/10.7708/ijtte2021.11(3).03

Stanković, M., Stević, Ž., Das, D. K., Subotić, M., Pamučar, D. (2020). A New Fuzzy MARCOS Method for Road Traffic Risk Analysis. Mathematics, 8 (3), 457. doi: https://doi.org/10.3390/math8030457

Ulutaş, A., Karabasevic, D., Popovic, G., Stanujkic, D., Nguyen, P. T., Karaköy, Ç. (2020). Development of a Novel Integrated CCSD-ITARA-MARCOS Decision-Making Approach for Stackers Selection in a Logistics System. Mathematics, 8 (10), 1672. doi: https://doi.org/10.3390/math8101672

Stević, Ž., Brković, N. (2020). A Novel Integrated FUCOM-MARCOS Model for Evaluation of Human Resources in a Transport Company. Logistics, 4 (1), 4. doi: https://doi.org/10.3390/logistics4010004

Anysz, H., Nicał, A., Stević, Ž., Grzegorzewski, M., Sikora, K. (2020). Pareto Optimal Decisions in Multi-Criteria Decision Making Explained with Construction Cost Cases. Symmetry, 13 (1), 46. doi: https://doi.org/10.3390/sym13010046

Brian Rowe, W. (2014). Principles of Modern Grinding Technology. William Andrew. doi: https://doi.org/10.1016/c2013-0-06952-6

Gunantara, N. (2018). A review of multi-objective optimization: Methods and its applications. Cogent Engineering, 5 (1), 1502242. doi: https://doi.org/10.1080/23311916.2018.1502242

Nguyen, N.-T., Trung, D. (2021). Combination of Taguchi method, MOORA and COPRAS techniques in multi-objective optimization of surface grinding process. Journal of Applied Engineering Science, 19 (2), 390–398. doi: https://doi.org/10.5937/jaes0-28702

👁 178
⬇ 187
How to Cite
Thinh, H. X., & Trung, D. D. (2022). A research on application of the measurement of alternatives and ranking according to compromise solution method for multi-criteria decision making in the grinding process. EUREKA: Physics and Engineering, (2), 101-110. https://doi.org/10.21303/2461-4262.2022.002120