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Additive manufacturing is a widely used process consisting in the building of a three-dimensional (3D) object from a model projected on a computer, adding the material layer-by-layer. This technology allows the printing of complex shape objects and is being increasingly adopted by the aircraft industry, medical implants, jewelry, footwear, automotive, fashion products, among others. The build orientation optimization of 3D models has a great influence on costs and surface quality when printing three-dimensional objects. In this work, three build orientation optimization problems are studied: single objective problem, bi-objective problem and many-objective problem. To this end, three quality measures are applied: the support area, the build time and the surface roughness, for the Car Hoodvent model. First, a single-objective optimization problem is presented and solved by the genetic algorithm, obtaining optimal solutions for each objective function. Then, the study of the bi-objective optimization problem is carried out for each pair of two objectives and some representative trade-off solutions are identified. Finally, the study of the many objective optimization problem, considering the three measures optimized simultaneously, is presented with some more optimal solutions found. The bi-objective and many-objective problems are solved by a multi-objective genetic algorithm. For a better analysis and comparison of the solutions found, the Pareto fronts are used, enabling a better visualization of the solutions between the objectives. This study aims to assist the decision-maker in choosing the best part print orientation angles according to his/her preferences. The optimal solutions found confirmed the effectiveness of the proposed approach. info:eu-repo/semantics/publishedVersion |
