Cutting Force Prediction of Ti6Al4V using a Machine Learning Model of SPH Orthogonal Cutting Process Simulations
The prediction of machining processes is a challenging task and usually requires a large experimental basis. These experiments are time-consuming and require manufacturing and testing of different tool geometries at various process conditions to find optimum machining settings. In this paper, a mach...
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| Principais autores: | , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Publishing House of Wrocław Board of Scientific Technical Societies Federation NOT
2022-03-01
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| Series: | Journal of Machine Engineering |
| Assuntos: | |
| Acceso en liña: | http://jmacheng.not.pl/Cutting-Force-Prediction-of-Ti6Al4V-using-a-Machine-Learning-Model-of-SPH-Orthogonal,147201,0,2.html |
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