| Autor: |
Paramjit Thakur, Fauzia Siddiqui |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
International Journal of Engineering Sciences. 11 |
| ISSN: |
0976-6693 |
| DOI: |
10.36224/ijes.110405 |
| Popis: |
Al 7075 T6 is one of the highest strength aluminum alloys in 7000 series family which is used in highly stressed structural parts of aircrafts. The high surface roughness lowers the fatigue resistance and also affects the quality of the parts. Hence, this work deals with the application of teaching learning based optimization to minimize the roughness in the CNC end milling process. Here, taguchi L9 orthogonal array is used as experimental design. The depth of cut, feed and speed are used as control factors with three levels each and roughness as the response. The regression model was developed to find the effect of process parameters on response. The regression model was used by Teaching Learning Based Optimization (TLBO) algorithm and optimum process parameters were obtained. The optimal process parameters obtained by TLBO gave 60% reduction in roughness as compared to that given by initial setting of parameters used for machining of this material. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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