The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC
This paper presents the use of TOPSIS, a multi-criteria decision-making model combined with the Taguchi method to find the optimum milling parameters. TOPSIS is the Technique for Order Preference by Similarity to the Ideal Solution and shows the value of closeness to the positive ideal solution. Thi...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
|
| Series: | Metals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4701/12/11/1796 |
| _version_ | 1797467272745320448 |
|---|---|
| author | Saeid Kamalizadeh Seyed Ali Niknam Marek Balazinski Sylvain Turenne |
| author_facet | Saeid Kamalizadeh Seyed Ali Niknam Marek Balazinski Sylvain Turenne |
| author_sort | Saeid Kamalizadeh |
| collection | DOAJ |
| description | This paper presents the use of TOPSIS, a multi-criteria decision-making model combined with the Taguchi method to find the optimum milling parameters. TOPSIS is the Technique for Order Preference by Similarity to the Ideal Solution and shows the value of closeness to the positive ideal solution. This study shows the optimum combination of process parameters using the shortest distance from the ideal solution. The surface roughness and flank tool wear were considered the objectives for simultaneous optimization. After converting multiple responses into a single response, the Taguchi method was used to analyze and determine the optimum machining parameters. According to reported studies, the initial wear behavior and initial cutting conditions have significant effects on the tool wear progress. Several initial cutting parameters can contribute to tool life and therefore can be used to improve both tool life and surface roughness. However, the cutting speed may significantly affect tool wear and ultimate tool life. In this study, an innovative solution was proposed for interrupted machining with two different cutting speeds. The first level cutting speed was used for 1 s and the second level was used for the rest of the process. The experimental results indicate that the initial speed followed by the feed rate significantly affects tool life. In addition, using the proposed strategy with different levels of cutting speed during machining operations led to improved tool life and surface roughness compared to conventional machining with uniform cutting speed throughout the entire process. |
| first_indexed | 2024-03-09T18:51:16Z |
| format | Article |
| id | doaj.art-d0584efd56b14860b7b489718f913b1d |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-09T18:51:16Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-d0584efd56b14860b7b489718f913b1d2023-11-24T05:51:15ZengMDPI AGMetals2075-47012022-10-011211179610.3390/met12111796The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMCSaeid Kamalizadeh0Seyed Ali Niknam1Marek Balazinski2Sylvain Turenne3Mechanical Engineering Department, Polytechnique Montreal, Montréal, QC H3T 1J4, CanadaMechanical Engineering Department, Polytechnique Montreal, Montréal, QC H3T 1J4, CanadaMechanical Engineering Department, Polytechnique Montreal, Montréal, QC H3T 1J4, CanadaMechanical Engineering Department, Polytechnique Montreal, Montréal, QC H3T 1J4, CanadaThis paper presents the use of TOPSIS, a multi-criteria decision-making model combined with the Taguchi method to find the optimum milling parameters. TOPSIS is the Technique for Order Preference by Similarity to the Ideal Solution and shows the value of closeness to the positive ideal solution. This study shows the optimum combination of process parameters using the shortest distance from the ideal solution. The surface roughness and flank tool wear were considered the objectives for simultaneous optimization. After converting multiple responses into a single response, the Taguchi method was used to analyze and determine the optimum machining parameters. According to reported studies, the initial wear behavior and initial cutting conditions have significant effects on the tool wear progress. Several initial cutting parameters can contribute to tool life and therefore can be used to improve both tool life and surface roughness. However, the cutting speed may significantly affect tool wear and ultimate tool life. In this study, an innovative solution was proposed for interrupted machining with two different cutting speeds. The first level cutting speed was used for 1 s and the second level was used for the rest of the process. The experimental results indicate that the initial speed followed by the feed rate significantly affects tool life. In addition, using the proposed strategy with different levels of cutting speed during machining operations led to improved tool life and surface roughness compared to conventional machining with uniform cutting speed throughout the entire process.https://www.mdpi.com/2075-4701/12/11/1796Ti-MMCmachiningtool lifeinitial tool wearcutting speedoptimization |
| spellingShingle | Saeid Kamalizadeh Seyed Ali Niknam Marek Balazinski Sylvain Turenne The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC Metals Ti-MMC machining tool life initial tool wear cutting speed optimization |
| title | The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC |
| title_full | The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC |
| title_fullStr | The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC |
| title_full_unstemmed | The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC |
| title_short | The Use of TOPSIS Method for Multi-Objective Optimization in Milling Ti-MMC |
| title_sort | use of topsis method for multi objective optimization in milling ti mmc |
| topic | Ti-MMC machining tool life initial tool wear cutting speed optimization |
| url | https://www.mdpi.com/2075-4701/12/11/1796 |
| work_keys_str_mv | AT saeidkamalizadeh theuseoftopsismethodformultiobjectiveoptimizationinmillingtimmc AT seyedaliniknam theuseoftopsismethodformultiobjectiveoptimizationinmillingtimmc AT marekbalazinski theuseoftopsismethodformultiobjectiveoptimizationinmillingtimmc AT sylvainturenne theuseoftopsismethodformultiobjectiveoptimizationinmillingtimmc AT saeidkamalizadeh useoftopsismethodformultiobjectiveoptimizationinmillingtimmc AT seyedaliniknam useoftopsismethodformultiobjectiveoptimizationinmillingtimmc AT marekbalazinski useoftopsismethodformultiobjectiveoptimizationinmillingtimmc AT sylvainturenne useoftopsismethodformultiobjectiveoptimizationinmillingtimmc |