Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS
In this study, the efficiency of integration between Taguchi and TOPSIS in multi-response optimi-zation of powder mixed electrical discharge machining (PMEDM) process was evaluated. The in-put parameters, such as workpiece and tool electrode material, polarity, pulse on time (ton), pulse off time (t...
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| Format: | Article |
| Language: | English |
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Growing Science
2018-10-01
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| Series: | International Journal of Data and Network Science |
| Subjects: | |
| Online Access: | http://www.growingscience.com/ijds/Vol2/ijdns_2018_10.pdf |
| _version_ | 1818237039482503168 |
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| author | Phan H. Nguyen Long T. Banh Viet. D. Bui Dung T. Hoang |
| author_facet | Phan H. Nguyen Long T. Banh Viet. D. Bui Dung T. Hoang |
| author_sort | Phan H. Nguyen |
| collection | DOAJ |
| description | In this study, the efficiency of integration between Taguchi and TOPSIS in multi-response optimi-zation of powder mixed electrical discharge machining (PMEDM) process was evaluated. The in-put parameters, such as workpiece and tool electrode material, polarity, pulse on time (ton), pulse off time (toff), Current (I) and powder concentration have been selected to optimize two responses; namely surface roughness (Ra) and surface hardness (HV). The results show that titanium powder mixed dielectric fluid improves multi-response optimization efficiency in PMEDM. In addition, machining conditions, such as tool electrode material, powder concentration, pulse on time, polarity, current density, A×G and B×G interactions play a very important role on S/N ratio of C* whereby powder concentration has the strongest influence. TOPSIS -Taguchi is a potential method for multi-response optimization in PMEDM. However, the optimal results using ANOVA analysis show that there is a necessity to have more studies in TOPSIS-Taguchi to improve the in-tegration efficiency between two methods for optimizing multiple responses in PMEDM. |
| first_indexed | 2024-12-12T12:19:25Z |
| format | Article |
| id | doaj.art-e6b0721039474b359a31a2bd7f19b898 |
| institution | Directory Open Access Journal |
| issn | 2561-8148 2561-8156 |
| language | English |
| last_indexed | 2024-12-12T12:19:25Z |
| publishDate | 2018-10-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Data and Network Science |
| spelling | doaj.art-e6b0721039474b359a31a2bd7f19b8982022-12-22T00:24:41ZengGrowing ScienceInternational Journal of Data and Network Science2561-81482561-81562018-10-012410911910.5267/j.ijdns.2018.9.001Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSISPhan H. NguyenLong T. BanhViet. D. BuiDung T. HoangIn this study, the efficiency of integration between Taguchi and TOPSIS in multi-response optimi-zation of powder mixed electrical discharge machining (PMEDM) process was evaluated. The in-put parameters, such as workpiece and tool electrode material, polarity, pulse on time (ton), pulse off time (toff), Current (I) and powder concentration have been selected to optimize two responses; namely surface roughness (Ra) and surface hardness (HV). The results show that titanium powder mixed dielectric fluid improves multi-response optimization efficiency in PMEDM. In addition, machining conditions, such as tool electrode material, powder concentration, pulse on time, polarity, current density, A×G and B×G interactions play a very important role on S/N ratio of C* whereby powder concentration has the strongest influence. TOPSIS -Taguchi is a potential method for multi-response optimization in PMEDM. However, the optimal results using ANOVA analysis show that there is a necessity to have more studies in TOPSIS-Taguchi to improve the in-tegration efficiency between two methods for optimizing multiple responses in PMEDM.http://www.growingscience.com/ijds/Vol2/ijdns_2018_10.pdfTaguchiTOPSISEDMPMEDMS/N ratioTitanium |
| spellingShingle | Phan H. Nguyen Long T. Banh Viet. D. Bui Dung T. Hoang Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS International Journal of Data and Network Science Taguchi TOPSIS EDM PMEDM S/N ratio Titanium |
| title | Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS |
| title_full | Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS |
| title_fullStr | Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS |
| title_full_unstemmed | Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS |
| title_short | Multi-response optimization of process parameters for powder mixed electro-discharge machining according to the surface roughness and surface micro-hardness using Taguchi-TOPSIS |
| title_sort | multi response optimization of process parameters for powder mixed electro discharge machining according to the surface roughness and surface micro hardness using taguchi topsis |
| topic | Taguchi TOPSIS EDM PMEDM S/N ratio Titanium |
| url | http://www.growingscience.com/ijds/Vol2/ijdns_2018_10.pdf |
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