Optimization algorithm of building orientation in LPBF based on teaching-learning-based optimization

In laser powder bed fusion (LPBF) process, the choice of printing direction is the key step of the layered construction process planning. The choice of printing direction will directly affect the forming quality and printing cost of the part. The printing direction of the part is usually manually selected by the operator, and the optimal construction direction cannot be determined before printing. Aiming at the problem of LPBF part orientation, a teaching-learning based algorithm (TLBO) based orientation optimization method for metal 3D printing parts was proposed from the perspective of printing cost. Firstly, according to the metal 3D printing process, a comprehensive cost model of LPBF process was established, which considered the volume of supporting structure, printing height and printing time of parts. Then, a multi-objective optimization model of printing direction and cost was established by transforming the geometric representation of STL model, and the optimal construction direction of parts was obtained by using TLBO for global search. The high cost of metal 3D printing process is solved and the automatic selection of forming direction is realized. Finally, the application of the proposed method is introduced in an example model, and the effectiveness and efficiency of the proposed method are proved by comparing with the generated print direction in commercial software Magics and the optimization direction of genetic algorithm (GA).