| Summary: | Over the years, rapid prototyping technologies have grown and have been implemented in many 3D model production companies. A variety of different additive manufacturing (AM) techniques are used in rapid prototyping. AM refers to a process by which digital 3D design data is used to build up a component in layers by depositing material. Several high-quality parts are being created in various engineering materials, including metal, ceramics, polymers and their combinations in the form of composites, hybrids, or functionally classified materials. The orientation of 3D models is very important since it can have a great influence on the surface quality characteristics, such as process planning, post-processing, processing time and cost. Thus, the identification of the optimal build orientation for a part is one of the main issues in AM. The quality measures to optimize the build orientation problem may include the minimization of the surface roughness, build time, need of supports, maximize of the part stability in building process or part accuracy, among others. In this paper, a multi-objective approach was applied to a computer-aided design model using MATLAB® multi-objective genetic algorithm, aiming to optimize the support area, the staircase effect and the build time. Preliminary results show the effectiveness of the proposed approach.
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