Parametric optimization of cutting parameters for micro-machining of titanium Grade-12 alloy using statistical techniques
The main aim of this research work is to examine the impact of machining parameters on the tool wear, machining forces and surface quality in micro-machining of light weight titanium Gr-12 alloy using statistical technique. The Taguchi method has been efficiently used here to associate input variabl...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
KeAi Communications Co., Ltd.
2022
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/cd87ac9e49ef408eb0e1595a06136cd3 |
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| Sumario: | The main aim of this research work is to examine the impact of machining parameters on the tool wear, machining forces and surface quality in micro-machining of light weight titanium Gr-12 alloy using statistical technique. The Taguchi method has been efficiently used here to associate input variables and output response relationship and also to evaluate the parametric effects by ANOVA analysis. The test results using a linear regression model were correlated. The output results indicated that the depth of cut and speed of cutting have substantial effects on machining force, surface quality and tool wear. The obtained results have been confirmed through confirmation tests with less than 6% error value. It proves that the projected statistical approach is reliable, and is an optimization and typical model for prediction of micro milling parameters for titanium Gr-12 alloy. |
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