Additive manufacturing is the method for fabricating the components
effectively. The components fabricated by additive manufacturing process have wider
applications in various domains. Fusion deposition modeling is one of the additive
manufacturing methodologies that has been used for fabricating the components.
Generating CAD model occupies the first and foremost step in this process, followed
by printing of the designed model through fusion deposition extruders. The preparation
of components through fused deposition makes it easier for the complex as well as
most intricated shaped components, which is difficult in the case of existing
conventional manufacturing practices. This liberty propels the effective utilization of
additive manufacturing techniques in various fields ranging from the automotive to
aerospace industries. This increasing demand turns the focus towards the selection of
precise modeling techniques while selecting the process parameters in the fused
deposition techniques. The present work mainly focused on the selection of best
models for the fused deposition modeling and the comparative analysis between
multiple regression analysis and ANFIS models for the selected parameters.
Keywords: 3D printing, Additive manufacturing, ANFIS model, Artificial neural
network, Comparative analysis, Fused deposition modeling, GRG, Optimization, Part
thickness, Prediction, Printing time, Regression models, Response analysis, Surface
roughness.
