3D printing build orientation optimization for flexible support platform. Issue 1 (3rd September 2019)

• Record Type: Journal Article
• Authors: Shen, Hongyao; Ye, Xiaoxiang; Xu, Guanhua; Zhang, Linchu; Qian, Jun; Fu, Jianzhong
• Is Part Of: Rapid prototyping journal. Volume 26:Issue 1(2020)
• Page Start: 59
• Page End: 72
• Publication Date: 2019-09-03
• Subjects: Algorithms -- Fused deposition modeling -- Process planning -- 3D printing -- Particle swarm optimization -- Orientation -- Equipment -- Build orientation optimization -- Flexible support platform -- Support structure reduction; Engineering design -- Periodicals; 620.004205
• DOI: 10.1108/RPJ-09-2018-0252
• Languages: English
• ISSNs: 1355-2546

Abstract

Abstract : Purpose: During the 3D printing process, the model needs to add a support structure to ensure structural stability. Excessive support structure reduces printing efficiency and results in material cost. A flexible support platform for 3 D printing has been designed. It can form an external support structure to replace the original support structure. This paper aims to study the influence of a model's build orientation on properties when the model is printed on the platform, aiming to provide users with suitable solutions. Design/methodology/approach: A fitness function for estimating the support structure with a support length is constructed. The particle swarm optimization (PSO) algorithm is modified and applied to find the build orientation that minimizes the support structure. However, when the model is printed on the platform, the build orientation of the minimum support structure enhances the complexity of the working path, resulting in an increase of printing time, which needs to be avoided. This paper applies a multi-objective particle swarm optimization (MOPSO) algorithm to minimize the support structure while minimizing printing time. The Pareto solution is obtained by the algorithm. Findings: It is found that the model that has the cantilever structure can reduce more support structure after optimization on the platform, when there is surface quality requirement. When there is no limit, the modified algorithm can minimize the support structure of each model. Considering support structure and printing time, the MOPSO algorithm can easily get optimization results to guide the practical work. Originality/value: This paper optimizes the model's build orientation on the flexible support platform by PSO, thereby reducing material cost and improving work efficiency.