Genetic-algorithm-based multi-objective optimization of the build orientation in stereolithography

Build orientation is an important fabrication parameter in layer manufacturing (LM) since it affects the part fabrication accuracy, cost, and time. Despite its importance, orientation selection relies quite heavily on the experience and skill of the operator of the LM system, which does not guarantee optimality of the decision. In the present work, a decision support system that automates the orientation selection task is proposed. The proposed system utilizes genetic algorithms and multi-criteria optimization techniques for the definition of (near) optimum build orientation for parts fabricated with stereolithography. Build time, surface roughness, and post-processing time are considered as the main optimization criteria.