Optimal part deposition orientation in fast design methodology by using a multicriteria genetic algorithm

In rapid prototyping processes, the deposition orientation of the part is very important as it affects part surface quality, production time and the requirement for support structure and hence cost. Depositing the part with thinner slices results in a larger build time. At the same time, if a large slice thickness is chosen, the surface finish is very poor due to stair-stepping. These are two contradicting issues and are tackled by using adaptive slicing. In adaptive slicing, slice thickness is calculated based on local geometry of the computer-aided design model and rapid prototyping machine specifications. Even though adaptive slicing controls part surface quality by compromising on build time for a deposition orientation, an optimum orientation can further reduce build time and enhance part surface quality. In the present work, an attempt has been made to determine the optimal part deposition orientations by considering two objective functions at a time, namely average part surface roughness (average part surface quality) and build time. The two objectives are minimized simultaneously using a multicriteria genetic algorithm.