FEATURE-BASED SUPPORT GENERATION FOR OPTIMUM PART DEPOSITION ORIENTATION IN FDM

Support generation is the key technology for Fused Deposition Modeling (FDM) machine. It is dependent on part deposition orientation. Various part deposition orientation results in formation of different support and non-support features. Present work focuses on extracting the support features containing Externally-Supported Features (ESF) which is able to determine the volume and number of support structure. These information are utilized to obtain the optimum part deposition orientation. Artificial Neural Network (ANN) is used to determine the optimum solution. Predictions of the present methodology are in agreement with the results published earlier. The methodology proposed in this work is used to obtain the optimum part deposition orientation automatically and can be implemented in FDM technology.