Optimize 3D Printing Material Process Parameters: A Case On Regression And Neural Network

This study optimizes the number of shells, layer thickness, printing speed and infill density while taking the single response of tensile strength into account. The range 3-5 nos for no of shell, 0.2- 3 mm for layer thickness, 40-80 m/sec for infill density and printing speed varying from 3600-6000 m/sec with experimental trails towards L9 orthogonal array were carried out. When using the ideal process parameters, the single response technique exhibits the best convergences where the maximum tensile strength results are obtained. Further, in order to identify important variable FDM process parameters, Regression and Artificial Neural Network as chosen for modelling and validated this model using SPSS.