Toolpath planning for additive manufacturing using sliced model decomposition and metaheuristic algorithms

Abstract

Fabrication efficiency has long been a challenge for additive manufacturing. Standard toolpath generation processes usually give rise to a significant number of non-productive motions that undermine production efficiency and degrade part quality due to frequent acceleration and deceleration in wasted motions. In this paper, we introduce an optimized toolpath generation process that comprises of decomposition of sliced model and optimization of fabrication sequences to minimize non-productive toolpaths. Unlike standard toolpaths, optimized toolpaths carry out fabrication of multiple objects in a staggered sequence to maximize manufacturing efficiency. To tackle the problem of interference between a printhead and objects due to changes in the fabrication sequence of layered depositions, an algorithm that adaptively determines collision-free heights is developed. Additionally, sliced model decomposition considerably reduces the number of entities for optimization. The computational cost involved in toolpath optimization is independent of slicing interval; therefore, the effectiveness and applicability of the proposed optimization approach are well maintained for small slicing intervals. Benchmarks are analyzed to demonstrate the effectiveness and robustness of the proposed toolpath planning approach, and two physical experiments are carried out using fused deposition modeling (FDM) and direct metal deposition (DMD) technologies. Non-productive toolpaths are reduced remarkably, and the desired fabrication quality is achieved for both non-metal and metal structures.