Logistic regression model for the grooving process of hybrid polyester resin composite materials reinforced with natural fibers and fiberglass

Greencomposites materials are being integrate into the manufacturing of products in diverse fields. For its assembly, are required secondary manufacturing processes such as the machining of slots and holes. In these processes, the greencomposites present great sensitivity to their manufacture. For the study of this concept, an experimental design was developed to analyze the grooving process and verify the effects of the cutting parameters with two types of tools (HSS and HSC) on surface quality (Ra) and the delamination factor (Fd) of the material. An analysis of the experiment was carried out to verify the significant effects of the different factors involved, in addition a multiple linear regression analysis and binomial logistic regression to predict surface quality and delamination in other conditions. The results obtained show the logistic regression model gave a better prediction for the grooving process of the greencomposites, both for the surface roughness and for the delamination factor. Finally, this study concludes that the carbide tool (HSC) has better surface quality with respect to the conventional tool of high speed steel (HSS).