Multi-criteria GA-based Pareto optimization of building direction for rapid prototyping

Selection of a building direction is an important step for rapid prototyping regardless of the specific processes used to create the part. It involves the consideration of multi-factors that have influences on surface quality, build efficiency and support structure, etc. Contemporary approaches did not consider the global directional space to search for the optimal building direction. In this paper, we use a multi-sphere model for multi-criteria optimization of building direction in rapid prototyping. Each sphere represents the global directional space for one optimization criterion, and is obtained by uniformly discretizing the surface of a unit sphere. Optimization is then conducted over each discretized spherical surface for each criterion. Two objectives, theoretical volume deviation (TVD) and part height are simultaneously optimized using genetic algorithm. TVD is computed to evaluate the volumetric error along each building direction in a general way. The Pareto front is computed as well in order to study the competing effect from these two criteria. At the end of the paper, examples are presented to show the effectiveness of the method.