Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods
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...
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| Format: | Article |
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MDPI AG
2022-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/8/3720 |
| _version_ | 1797437054314872832 |
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| author | Huu-Quang Nguyen Van-Tung Nguyen Dang-Phong Phan Quoc-Hoang Tran Ngoc-Pi Vu |
| author_facet | Huu-Quang Nguyen Van-Tung Nguyen Dang-Phong Phan Quoc-Hoang Tran Ngoc-Pi Vu |
| author_sort | Huu-Quang Nguyen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T11:13:27Z |
| format | Article |
| id | doaj.art-e932244587a84c22b983039b984301eb |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T11:13:27Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-e932244587a84c22b983039b984301eb2023-12-01T00:37:20ZengMDPI AGApplied Sciences2076-34172022-04-01128372010.3390/app12083720Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA MethodsHuu-Quang Nguyen0Van-Tung Nguyen1Dang-Phong Phan2Quoc-Hoang Tran3Ngoc-Pi Vu4Faculty of Mechanical Engineering, University of Economics–Technology for Industries, Ha Noi 11622, VietnamFaculty of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen 251750, VietnamNational Research Institute of Mechanical Engineering, Hanoi 511309, VietnamFaculty of Mechanical Engineering, Nguyen Tat Thanh University, Ho Chi Minh City 754000, VietnamFaculty of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen 251750, VietnamMulti-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.https://www.mdpi.com/2076-3417/12/8/3720PMEDMmulti-criteria decision makingMARCOSTOPSISMAIRCAMEREC |
| spellingShingle | Huu-Quang Nguyen Van-Tung Nguyen Dang-Phong Phan Quoc-Hoang Tran Ngoc-Pi Vu Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods Applied Sciences PMEDM multi-criteria decision making MARCOS TOPSIS MAIRCA MEREC |
| title | Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods |
| title_full | Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods |
| title_fullStr | Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods |
| title_full_unstemmed | Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods |
| title_short | Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods |
| title_sort | multi criteria decision making in the pmedm process by using marcos topsis and mairca methods |
| topic | PMEDM multi-criteria decision making MARCOS TOPSIS MAIRCA MEREC |
| url | https://www.mdpi.com/2076-3417/12/8/3720 |
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