Proposing an improved model of linear regression to predict product quality for Fused Deposition Modeling (FDM) depending on the input parameters

Abstract

Fused deposition modeling (FDM) is one of the popular types of additive manufacturing, which is characterized by low costs and speed of production, but this type contains many manufacturing parameters (more than 20 parameters). Any change in the values of these parameters has a direct effect on product quality and mechanical properties. In previous studies, the experimental approach was relied upon to demonstrate the effect of processing parameters on product quality. In this article, an improved model based on the linear regression was proposed to predict product quality (strength tensile strength) for fused deposition modeling (FDM) based on processing parameters, and comparing the predicted results with the real results.