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Enhancing handheld polishing machine selection: anintegrated approach of marcos methods and weightdetermination techniques
Authors:
Nguyen Xuan Truong1
,
Aleksandar Ašonja2
,
Do Duc Trung1
1Faculty of Mechanical Engineering, Hanoi University of Industry, Hanoi City, 100000, Vietnam
2Faculty of Economics and Engineering Management, University Business Academy, Novi Sad, Serbia
Received: 1 June 2023
Revised: 3 September 2023
Accepted: 15 September 2023
Published: 30 September 2023
Abstract:
The handheld polishing machine plays a pivotal role in enhancing the aesthetics of household products, making it a vital device. This research aims to identify the optimal option among the available types. Thirteen diverse handheld polishing machines were utilized for evaluation. Six key criteria were carefully chosen to assess each alternative, encompassing price, capacity, polishing disc diameter, polishing disc speed at idle, machine weight, and supplier warranty period. The relative importance of these criteria was determined using four distinct methods: Equal weighting, RS (Rank Sum) weighting, ROC (Rank Order Centroid) weighting, and Entropy weighting. The MARCOS (Measurement Alternatives and Ranking according to COmpromise Solution) method was employed to rank the alternatives. Remarkably, all four different weighting methods consistently led to the same conclusion, identifying the best and worst options.
Keywords:
Selection of handheld polishing machine, MARCOS method, Equal weighting, RS weighting, ROC weighting, Entropy weighting
References:
[1] C. Zopounidis, M. Doumpos, Multiple Criteria Decision Making – Applications in Management and Engineering. Springer, 2017. https://doi.org/10.1007/978-3-319-39292-9
[2] D.D. Trung, Development of data normalization methods for multi-criteria decision making: applying for MARCOS method. Manufacturing Review, 9(22), 2022:1-15. https://doi.org/10.1051/mfreview/2022019
[3] D.D. Trung, Multi-criteria decision making under the MARCOS method and the weighting methods: applied to milling, grinding and turning processes. Manufacturing Review, 9(3), 2022: 1-13.
https://doi.org/10.1051/mfreview/2022003
[4] N.H. Son, T.T. Hieu, Selection of welding robot by multi-criteria decisionmaking method. Eastern-European Journal of Enterprise Technologies, 121(3), 2023: 66-72. https://doi.org/10.15587/1729-4061.2023.269026
[5] N.A. Osintsev, Multi-Criteria Decision-Making Methods in Green Logistics. World of Transport and Transportation, 19(5), 2021: 231-240. https://doi.org/10.30932/1992-3252-2021-19-5-13
[6] S. Miskic, S. Tadic, Z. Stevic, M. Krstic, V. Roso, A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies’ Applicability in Logistics Centers. Journal of Mathematics, 2023, 2023: 3532862. https://doi.org/10.1155/2023/3532862
[7] D. Pamucar, A.E. Torkayesh, S. Biswas, Supplier selection in healthcare supply chain management during the COVID-19 pandemic: a novel fuzzy rough decision-making approach. Annals of Operations Research, 328, 2023: 979-1019. https://doi.org/10.1007/s10479-022-04529-2
[8] A. Ghosh, A. Sarkar, M. Dey, B. Guha, S. Jana, N. Ghorui, Analyzing Efficiency of Indian Life Insurance Companies using DEA and SEM. Turkish Journal of Computer and Mathematics Education, 12(12), 2021: 3897-3919.
[9] F. Ecer, D. Pamucar, MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services. Applied Soft Computing Journal, 104, 2021: 107199. https://doi.org/10.1016/j.asoc.2021.107199
[10] D.D. Trung, N H. Son, T.T. Hieu, V.T.N. Uyen, DOE-MARCOS: a new approach to multi-criteria decision making. Journal of Applied Engineering Science, 21(1) 2023: 263-274. https://doi.org/10.5937/jaes0-40221
[11] B. Matic, M. Marinkovic, S. Jovanovic, S. Sremac, Z. Stevic, Intelligent Novel IMF D- SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure. Buildings, 12(7), 2022: 1059. https://doi.org/10.3390/buildings12071059
[12] M. Stankovic, Z. Stevic, D. K. Das, M. Subotic, D. Pamucar, A New Fuzzy MARCOS Method for Road Traffic Risk Analysis. Mathematics, 8(3), 2020: 457. https://doi.org/10.3390/math8030457
[13] R. Lukic, Application of MARCOS method in evaluation of efficiency of trade companies in Serbia. Ekonomski pogledi, 24(1), 2022: 1-14. https://doi.org/10.5937/ep24-38921
[14] D.T. Birkocak, E.Acar, A.Ç. Bakadur, B. Ütebay, A. Özdağoğlu An Application of the MARCOS Method Within the Framework of Sustainability to Determine the Optimum Recycled Fibre-Containing Fabric. Fibers and Polymers, 24, 2023: 2595–2608. https://doi.org/10.1007/s12221-023-00197-6
[15] H. Wang, K. Ullah, T-spherical uncertain linguistic MARCOS method based on generalized distance and Heronian mean for multi-attribute group decision-making with unknown weight information. Complex & Intelligent Systems, 9, 2023: 1837-1869. https://doi.org/10.1007/s40747-022-00862-y
[16] C.-N. Wang, T.T.T. Nguyen, T.-T. Dang, N.-A.-T. Nguyen, A Hybrid OPA and Fuzzy MARCOS Methodology for Sustainable Supplier Selection with Technology 4.0 Evaluation. Processes, 10(11), 2022: 2351. https://doi.org/10.3390/pr10112351
[17] R. Dwivedi, K. Prasad, P.K. Jha, S. Singh, An Integrated CRITIC-MARCOS Technique for Analysing the Performance of Steel Industry. In K. Kalita, R. Ghadai, X. Gao (Eds.). Data- Driven Optimization of Manufacturing Processes, 2021: 115-127. htps://doi.org/10.4018/978-1-7998-7206-1.ch008
[18] M. Kovač, S. Tadić, M. Krstić, M.B. Bouraima, Novel Spherical Fuzzy MARCOS Method for Assessment of Drone-Based City Logistics Concepts. Complexity, 2021, 2021: 2374955.
https://doi.org/10.1155/2021/2374955
[19] E. Çakır, M.A. Taş, Z. Ulukan, Neutrosophic Fuzzy MARCOS Approach for Sustainable Hybrid Electric Vehicle Assessment. 2021 IEEE International Conference on Systems, Man, and Cybernetics, 7-20 October 2021, Melbourne, Australia 2022, 21456497. https://doi.org/10.1109/SMC52423.2021.9659199
[20] S. Chakraborty, R. Chattopadhyay, S. Chakraborty, An integrated D-MARCOS method for supplier selection in an iron and steel industry. Decision Making: Applications in Management and Engineering, 3(2), 2020: 49-69. https://doi.org/10.31181/dmame2003049c
[21] M. Khosravi, A. Haqbin, Z. Zare, P. Shojaei, Selecting the most suitable organizational structure for hospitals: an integrated fuzzy FUCOM-MARCOS method. Cost Effectiveness and Resource Allocation, 20, 2022: 29. https://doi.org/10.1186/s12962-022-00362-3
[22] Z. Stevic, D. Pamucar, A. Puska, P. Chatterjee, Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS). Computers & Industrial Engineering, 140, 2020: 106231.
https://doi.org/10.1016/j.cie.2019.106231
[23] D.D. Trung, Application of TOPSIS and PIV methods for multi-criteria decision making in hard turning process. Journal of Machine Engineering, 21(4), 2021: 57-71. https://doi.org/10.36897/jme/142599
[24] D.D. Trung, H.X. Thinh, 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), 2021: 443-456. https://doi.org/10.14743/apem2021.4.412
[25] https://dienmayhaianh.vn/san-pham/may- danh-bong-c340.html (Accessed: 22 May 2023).
[26] D.N. Markatos, S. Malefaki, S.G. Pantelakis, Sensitivity Analysis of a Hybrid MCDM Model for Sustainability Assessment-An Example from the Aviation Industry. Aerospace, 10(4), 2023: 385.
https://doi.org/10.3390/aerospace10040385
[27] H.A. Dağıstanlı, An Integrated Fuzzy MCDM and Trend Analysis Approach for Financial Performance Evaluation of Energy Companies in Borsa Istanbul Sustainability Index. Journal of Soft Computing and Decision Analytics, 1(1), 2023: 39-49. https://doi.org/10.31181/jscda1120233.
© 2023 by the authors. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 1
March 2025
Last Edition
Volume 10
Number 1
March 2025
How to Cite
N.X. Truong, A. Ašonja, D.D. Trung, Enhancing Handheld Polishing Machine Selection: An Integrated Approach of MACROS Methods and Weight Determination Techniques. Applied Engineering Letters, 8(3), 2023: 131–138.
https://doi.org/10.18485/aeletters.2023.8.3.5
More Citation Formats
Truong, N.X, Ašonja, A. & Trung, D.D. (2023). Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques. Applied Engineering Letters, 8(3), 131–138. https://doi.org/10.18485/aeletters.2023.8.3.5
Nguyen Xuan Truong, et al. “Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques.” Applied Engineering Letters, vol. 8, no. 3, 2023, pp. 131–38, https://doi.org/10.18485/aeletters.2023.8.3.5.
Nguyen Xuan Truong, Aleksandar Ašonja, and Do Duc Trung. 2023. “Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques.” Applied Engineering Letters 8 (3): 131–38. https://doi.org/10.18485/aeletters.2023.8.3.5.
Truong, N.X, Ašonja, A. and Trung, D.D. (2023). Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques. Applied Engineering Letters, 8(3), pp.131–138. doi: 10.18485/aeletters.2023.8.3.5.
Enhancing handheld polishing machine selection: anintegrated approach of marcos methods and weightdetermination techniques
Authors:
Nguyen Xuan Truong1
,
Aleksandar Ašonja2
,
Do Duc Trung1
1Faculty of Mechanical Engineering, Hanoi University of Industry, Hanoi City, 100000, Vietnam
2Faculty of Economics and Engineering Management, University Business Academy, Novi Sad, Serbia
Received: 1 June 2023
Revised: 3 September 2023
Accepted: 15 September 2023
Published: 30 September 2023
Abstract:
The handheld polishing machine plays a pivotal role in enhancing the aesthetics of household products, making it a vital device. This research aims to identify the optimal option among the available types. Thirteen diverse handheld polishing machines were utilized for evaluation. Six key criteria were carefully chosen to assess each alternative, encompassing price, capacity, polishing disc diameter, polishing disc speed at idle, machine weight, and supplier warranty period. The relative importance of these criteria was determined using four distinct methods: Equal weighting, RS (Rank Sum) weighting, ROC (Rank Order Centroid)weighting, and Entropy weighting. The MARCOS (MeasurementAlternatives and Ranking according to COmpromise Solution) method was employed to rank the alternatives. Remarkably, all four different weighting methods consistently led to the same conclusion, identifying the best and worst options.
Keywords:
Selection of handheld polishing machine, MARCOS method, Equal weighting, RS weighting, ROC weighting, Entropy weighting
References:
[1] C. Zopounidis, M. Doumpos, Multiple Criteria Decision Making – Applications in Management and Engineering. Springer, 2017. https://doi.org/10.1007/978-3-319-39292-9
[2] D.D. Trung, Development of data normalization methods for multi-criteria decision making: applying for MARCOS method. Manufacturing Review, 9(22), 2022:1-15. https://doi.org/10.1051/mfreview/2022019
[3] D.D. Trung, Multi-criteria decision making under the MARCOS method and the weighting methods: applied to milling, grinding and turning processes. Manufacturing Review, 9(3), 2022: 1-13.
https://doi.org/10.1051/mfreview/2022003
[4] N.H. Son, T.T. Hieu, Selection of welding robot by multi-criteria decisionmaking method. Eastern-European Journal of Enterprise Technologies, 121(3), 2023: 66-72. https://doi.org/10.15587/1729-4061.2023.269026
[5] N.A. Osintsev, Multi-Criteria Decision-Making Methods in Green Logistics. World of Transport and Transportation, 19(5), 2021: 231-240. https://doi.org/10.30932/1992-3252-2021-19-5-13
[6] S. Miskic, S. Tadic, Z. Stevic, M. Krstic, V. Roso, A Novel Hybrid Model for the Evaluation of Industry 4.0 Technologies’ Applicability in Logistics Centers. Journal of Mathematics, 2023, 2023: 3532862. https://doi.org/10.1155/2023/3532862
[7] D. Pamucar, A.E. Torkayesh, S. Biswas, Supplier selection in healthcare supply chain management during the COVID-19 pandemic: a novel fuzzy rough decision-making approach. Annals of Operations Research, 328, 2023: 979-1019. https://doi.org/10.1007/s10479-022-04529-2
[8] A. Ghosh, A. Sarkar, M. Dey, B. Guha, S. Jana, N. Ghorui, Analyzing Efficiency of Indian Life Insurance Companies using DEA and SEM. Turkish Journal of Computer and Mathematics Education, 12(12), 2021: 3897-3919.
[9] F. Ecer, D. Pamucar, MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services. Applied Soft Computing Journal, 104, 2021: 107199. https://doi.org/10.1016/j.asoc.2021.107199
[10] D.D. Trung, N H. Son, T.T. Hieu, V.T.N. Uyen, DOE-MARCOS: a new approach to multi-criteria decision making. Journal of Applied Engineering Science, 21(1) 2023: 263-274. https://doi.org/10.5937/jaes0-40221
[11] B. Matic, M. Marinkovic, S. Jovanovic, S. Sremac, Z. Stevic, Intelligent Novel IMF D- SWARA—Rough MARCOS Algorithm for Selection Construction Machinery for Sustainable Construction of Road Infrastructure. Buildings, 12(7), 2022: 1059. https://doi.org/10.3390/buildings12071059
[12] M. Stankovic, Z. Stevic, D. K. Das, M. Subotic, D. Pamucar, A New Fuzzy MARCOS Method for Road Traffic Risk Analysis. Mathematics, 8(3), 2020: 457. https://doi.org/10.3390/math8030457
[13] R. Lukic, Application of MARCOS method in evaluation of efficiency of trade companies in Serbia. Ekonomski pogledi, 24(1), 2022: 1-14. https://doi.org/10.5937/ep24-38921
[14] D.T. Birkocak, E.Acar, A.Ç. Bakadur, B. Ütebay, A. Özdağoğlu An Application of the MARCOS Method Within the Framework of Sustainability to Determine the Optimum Recycled Fibre-Containing Fabric. Fibers and Polymers, 24, 2023: 2595–2608. https://doi.org/10.1007/s12221-023-00197-6
[15] H. Wang, K. Ullah, T-spherical uncertain linguistic MARCOS method based on generalized distance and Heronian mean for multi-attribute group decision-making with unknown weight information. Complex & Intelligent Systems, 9, 2023: 1837-1869. https://doi.org/10.1007/s40747-022-00862-y
[16] C.-N. Wang, T.T.T. Nguyen, T.-T. Dang, N.-A.-T. Nguyen, A Hybrid OPA and Fuzzy MARCOS Methodology for Sustainable Supplier Selection with Technology 4.0 Evaluation. Processes, 10(11), 2022: 2351. https://doi.org/10.3390/pr10112351
[17] R. Dwivedi, K. Prasad, P.K. Jha, S. Singh, An Integrated CRITIC-MARCOS Technique for Analysing the Performance of Steel Industry. In K. Kalita, R. Ghadai, X. Gao (Eds.). Data- Driven Optimization of Manufacturing Processes, 2021: 115-127. htps://doi.org/10.4018/978-1-7998-7206-1.ch008
[18] M. Kovač, S. Tadić, M. Krstić, M.B. Bouraima, Novel Spherical Fuzzy MARCOS Method for Assessment of Drone-Based City Logistics Concepts. Complexity, 2021, 2021: 2374955.
https://doi.org/10.1155/2021/2374955
[19] E. Çakır, M.A. Taş, Z. Ulukan, Neutrosophic Fuzzy MARCOS Approach for Sustainable Hybrid Electric Vehicle Assessment. 2021 IEEE International Conference on Systems, Man, and Cybernetics, 7-20 October 2021, Melbourne, Australia 2022, 21456497. https://doi.org/10.1109/SMC52423.2021.9659199
[20] S. Chakraborty, R. Chattopadhyay, S. Chakraborty, An integrated D-MARCOS method for supplier selection in an iron and steel industry. Decision Making: Applications in Management and Engineering, 3(2), 2020: 49-69. https://doi.org/10.31181/dmame2003049c
[21] M. Khosravi, A. Haqbin, Z. Zare, P. Shojaei, Selecting the most suitable organizational structure for hospitals: an integrated fuzzy FUCOM-MARCOS method. Cost Effectiveness and Resource Allocation, 20, 2022: 29. https://doi.org/10.1186/s12962-022-00362-3
[22] Z. Stevic, D. Pamucar, A. Puska, P. Chatterjee, Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS). Computers & Industrial Engineering, 140, 2020: 106231.
https://doi.org/10.1016/j.cie.2019.106231
[23] D.D. Trung, Application of TOPSIS and PIV methods for multi-criteria decision making in hard turning process. Journal of Machine Engineering, 21(4), 2021: 57-71. https://doi.org/10.36897/jme/142599
[24] D.D. Trung, H.X. Thinh, 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), 2021: 443-456. https://doi.org/10.14743/apem2021.4.412
[25] https://dienmayhaianh.vn/san-pham/may- danh-bong-c340.html (Accessed: 22 May 2023).
[26] D.N. Markatos, S. Malefaki, S.G. Pantelakis, Sensitivity Analysis of a Hybrid MCDM Model for Sustainability Assessment-An Example from the Aviation Industry. Aerospace, 10(4), 2023: 385.
https://doi.org/10.3390/aerospace10040385
[27] H.A. Dağıstanlı, An Integrated Fuzzy MCDM and Trend Analysis Approach for Financial Performance Evaluation of Energy Companies in Borsa Istanbul Sustainability Index. Journal of Soft Computing and Decision Analytics, 1(1), 2023: 39-49. https://doi.org/10.31181/jscda1120233.
© 2023 by the authors. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 1
March 2025
Last Edition
Volume 10
Number 1
March 2025
How to Cite
N.X. Truong, A. Ašonja, D.D. Trung, Enhancing Handheld Polishing Machine Selection: An Integrated Approach of MACROS Methods and Weight Determination Techniques. Applied Engineering Letters, 8(3), 2023: 131–138.
https://doi.org/10.18485/aeletters.2023.8.3.5
More Citation Formats
Truong, N.X, Ašonja, A. & Trung, D.D. (2023). Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques. Applied Engineering Letters, 8(3), 131–138. https://doi.org/10.18485/aeletters.2023.8.3.5
Nguyen Xuan Truong, et al. “Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques.” Applied Engineering Letters, vol. 8, no. 3, 2023, pp. 131–38, https://doi.org/10.18485/aeletters.2023.8.3.5.
Nguyen Xuan Truong, Aleksandar Ašonja, and Do Duc Trung. 2023. “Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques.” Applied Engineering Letters 8 (3): 131–38. https://doi.org/10.18485/aeletters.2023.8.3.5.
Truong, N.X, Ašonja, A. and Trung, D.D. (2023). Enhancing Handheld Polishing Machine Selection: An Integrated Approach of Marcos Methods and Weight Determination Techniques. Applied Engineering Letters, 8(3), pp.131–138. doi: 10.18485/aeletters.2023.8.3.5.