Optimized Mask Image Projection for Solid Freeform Fabrication

Solid freeform fabrication (SFF) processes based on mask image projection have the potential to be fast and inexpensive. More and more research and commercial systems have been developed based on these processes. For the SFF processes, the mask image planning is an important process planning step. In this paper, we present an optimization based method for mask image planning. It is based on a light intensity blending technique called pixel blending. By intelligently controlling pixels’ gray scale values, the SFF processes can achieve a much higher $XY$ resolution and accordingly better part quality. We mathematically define the pixel blending problem and discuss its properties. Based on the formulation, we present several optimization models for solving the problem including a mixed-integer programming model, a linear programming model, and a two-stage optimization model. Both simulated and physical experiments for various CAD models are presented to demonstrate the effectiveness and efficiency of our method.