Comparison between artificial neural network and multiple regression for the pbkp_rediction of superficial roughness in dry turning

Abstract:

The simple regression and artificial neural network methods are techniques used in many industrial. This work developed two models in order to pbkp_redict the surface roughness in dry turning of AISI 316L stainless steel. In its implementation they were considered various cutting parameters such as cutting speed, feed, and machining time. The models obtained by both methods were compared to develop a full factorial design to increase reliability of the recorded values of roughness. The analysis can be checked by the values of coefficients of determination that the proposed models are able to pbkp_redict surface roughness. The obtained results show that the neural networks techniques is more accurate than the multiple regression techniques in this study.

Año de publicación:

2018

Keywords:

Fuente:

google