Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods
Source abstract
Abstract
Multi-criteria decision making (MCDM) is used to determine the best alternative among various options. It is of great importance as it hugely affects the efficiency of activities in life, management, business, and engineering. This paper presents the results of a multi-criteria decision-making study when using powder-mixed electrical discharge machining (PMEDM) of cylindrically shaped parts in 90CrSi tool steel. In this study, powder concentration, pulse duration, pulse off time, pulse current, and host voltage were selected as the input process parameters. Moreover, the Taguchi method was used for the experimental design. To simultaneously ensure minimum surface roughness (RS) and maximum material-removal speed (MRS) and to implement multi-criteria decision making, MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and MAIRCA (Multi-Attributive Ideal–Real Comparative Analysis) methods were applied. Additionally, the weight calculation for the criteria was calculated using the MEREC (Method based on the Removal Effects of Criteria) method. From the results, the best alternative for the multi-criteria problem with PMEDM cylindrically shaped parts was proposed.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Machining and Optimization Techniques · Manufacturing Process and Optimization · Multi-Criteria Decision Making
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Mechanical Engineering, University of Economics–Technology for Industries, Ha Noi 11622, Vietnam
Faculty of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen 251750, Vietnam
National Research Institute of Mechanical Engineering, Hanoi 511309, Vietnam
Faculty of Mechanical Engineering, Nguyen Tat Thanh University, Ho Chi Minh City 754000, Vietnam
References (26)
Show source-provided references
1. An in-depth review of theory of the TOPSIS method: An experimental analysis
2. The use of improved TOPSIS method based on experimental design and Chebyshev regression in solving MCDM problems10.1007/s10845-014-0973-9 ↗
3. A new approach for multiple objective decision making10.1016/0305-0548(93)90109-V ↗
4. Grinding Wheel Abrasive Material Selection Using Fuzzy TOPSIS Method10.1080/10426914.2012.700159 ↗
5. Stephen, D.S., and Sethuramalingam, P. (2022). Optimization of grinding titanium with 2%CNT-CBN wheel using TOPSIS. Mater. Manuf. Process.10.1080/10426914.2022.2039696 ↗
6. A multi-criteria decision-making in turning process using the MAIRCA, EAMR, MARCOS and TOPSIS methods: A comparative study
7. Multi-objective optimization using TOPSIS in turning of Al 6351 alloy10.1088/1757-899X/1112/1/012010 ↗
8. Application of TOPSIS and PIV methods for multi-criteria decision making in hard turning process10.36897/jme/142599 ↗
9. Parametric optimisation of EDM on Al-Cu/TiB2 in-situ metal matrix composites using TOPSIS method
10. Optimization of EDM process parameters for AlSiC- 20% SiC reinforced metal matrix composite with multi response using TOPSIS10.1016/j.matpr.2017.02.187 ↗
11. Multi Objective Optimization during Small Hole Electrical Discharge Machining (EDM) of Ti-6Al-4V using TOPSIS10.1016/j.matpr.2019.07.184 ↗
12. Multiresponse optimization of abrasive water jet cutting process parameters using TOPSIS approach10.1080/10426914.2014.994763 ↗
13. Optimisation of abrasive water jet cutting process parameters for AA5083-H32 aluminium alloy using fuzzy TOPSIS method
14. Zeng, Y.-P., Lin, C.-L., Dai, H.-M., Lin, Y.-C., and Hung, J.-C. (2021). Multi-Performance Optimization in Electrical Discharge Machining of Al2O3 Ceramics Using Taguchi Base AHP Weighted TOPSIS Method. Processes, 9.10.3390/pr9091647 ↗
15. Multi-criteria decision of W-powder mixed electro discharge drilling parameters using TOPSIS approach10.5755/j01.mech.25.1.22883 ↗
16. Multi-Objective Optimization of Process Parameters for Powder Mixed Electrical Discharge Machining of Inconel X-750 Alloy Using Taguchi-Topsis Approach10.2478/scjme-2021-0001 ↗
17. Pamučar, D.V., and Lukovac, V.L. (2014, January 9–10). Selection of railway level crossings for investing in security equipment using hybrid DEMATEL-MARICA model. Proceedings of the XVI International Scientific-expert Conference on Railways, Niš, Serbia.
18. Gigović, L., Pamučar, D., Bajić, Z., and Milićević, M. (2016). The Combination of Expert Judgment and GIS-MAIRCA Analysis for the Selection of Sites for Ammunition Depots. Sustainability, 8.10.3390/su8040372 ↗
19. Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS)10.1016/j.cie.2019.106231 ↗
20. Supplier selection for steelmaking company by using combined Grey-Marcos methods10.31181/dmame2003037b ↗
21. Multi-criteria decision making under the MARCOS method and the weighting methods: Applied to milling, grinding and turning processes
22. AHP-MARCOS, a hybrid model for selecting gears and cutting fluids10.1016/j.matpr.2021.11.142 ↗
23. Multi-Criteria Decision Making Using Preferential Selection Index in Titanium based Die-Sinking PMEDM10.7736/KSPE.2019.36.9.793 ↗
24. Parametric Optimization of Powder EDM Process using Grey Relational Analysis and TOPSIS
25. A review: Use of evolutionary algorithm for optimisation of machining parameters10.1007/s00170-021-07155-7 ↗
26. Assessment of distribution center locations using a multi-expert subjective–objective decision-making approach10.1038/s41598-021-98698-y ↗