Optimizing product manufacturability in 3D printing

3D printing has become a promising technique for industry production. This paper presents a research on the manufacturability optimization of discrete products under the influence of 3D printing technology. For this, we first model the problem using a tree structure, and then formulate it as a linear integer programming, where the total production time is to be minimized with the production cost constraint. To solve the problem, a differential evolution (DE) algorithm is developed, which automatically determines whether traditional manufacturing methods or 3D printing technology should be used for each part of the production. The algorithm is further quantitatively evaluated on a synthetic dataset, compared with the exhaustive search and alternating optimization solutions. Simulation results show that the proposed algorithm can well combine the traditional manufacturing methods and 3D printing technology in production, which is helpful to attain optimized product design and process planning concerning manufacture time. Therefore, it is beneficial to provide reference of the widely application and further industrialization of the 3D printing technology.