A polygons Boolean operations-based adaptive slicing with sliced data for additive manufacturing

In order to increase the efficiency of additive manufacturing, this paper proposes a novel adaptive slicing approach of sliced data with minimum thickness based on Boolean operations of polygons. It can greatly handle the balance between the build time and the surface precision of additive manufacturing. The proposed adaptive slicing is available for the single solid model, the support of additive manufacturing, and simultaneously manufactured multiple models. At first, the Boolean operations of polygons are used to gain the relationship of the adjacent layers to serve as the topological information. Second, two parameters are proposed to evaluate the precision of sliced surface: the ameliorative area ratio and variation of the cusp height. Ameliorative area ratio overcomes the drawbacks of original area deviation ration criteria and can work on the large and complex models. Variation of the cusp height makes the calculation of cusp height suitable for sliced data of model, and it is independent of the normal vector of surfaces. Third, the adaptive slicing is realized by removing unnecessary layers based on two parameters and the maximum allowable thickness. The thicknesses are times of the minimum thickness. Moreover, the adaptive slicing for support of additive manufacturing is developed through dividing the support into two parts according to its height and location. Slicing of multiple models is also proposed by choosing the maximum ameliorative area ratio and variation of the cusp height among all models in the same z level as the two parameters. Finally, the adaptive slicing for the three types is tested with some special models, and corresponding models are printed with FDM technology based on slicing results of the proposed approach. Results show that the proposed adaptive slicing approach is effective.