Intelligent Process Planning for Additive Manufacturing

Abstract

Abstract This paper introduces an intelligent approach for process planning of additive manufacturing (AM) in digital environment. A global adaptive slicing algorithm is developed and embedded in the introduced concept, which determines the layer thicknesses and widths based on the minimization of the deviations between the CAD model boundary and its stepped approximation. It is discussed that there are different metrics to measure the deviations such as cusp height, cusp volume and surface roughness criteria. A new criterion is developed to globally minimize the overall volumetric deviations of the final product from the desired geometric model. The proposed methodology uses the locally optimized layer thicknesses as the inputs to calculate the globally optimized layer thicknesses and the optimal contour for each layer. The global optimization problem is highly nonlinear that can be solved with a metaheuristic algorithm such as Simulated Annealing.