Abstract
Additive manufacturing (AM) has been increasingly used in the creation of three-dimensional objects, layer-by-layer, from three-dimensional (3D) computer-aided design (CAD) models. The problem of determining the 3D model printing orientation can lead to reduced amount of supporting material, build time, costs associated with the deposited material, labor costs, and other factors. This problem has been formulated and studied as a single-objective optimization problem. More recently, due to the existence and relevance of considering multiple criteria, multi-objective approaches have been developed.
In this paper, a multi-objective optimization approach is proposed to solve the part build orientation problem taking into account the support area characteristics and the build time. Therefore, the weighted Tchebycheff scalarization method embedded in the Electromagnetism-like Algorithm will be used to solve the part build orientation bi-objective problem of four 3D CAD models. The preliminary results seem promising when analyzing the Pareto fronts obtained for the 3D CAD models considered. Concluding, the multi-objective approach effectively solved the build orientation problem in AM, finding several compromise solutions.
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Acknowledgments
This work has been supported and developed under the FIBR3D project - Hybrid processes based on additive manufacturing of composites with long or short fibers reinforced thermoplastic matrix (POCI-01-0145-FEDER-016414), supported by the Lisbon Regional Operational Programme 2020, under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019.
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Matos, M.A., Rocha, A.M.A.C., Costa, L.A., Pereira, A.I. (2019). A Multi-objective Approach to Solve the Build Orientation Problem in Additive Manufacturing. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11621. Springer, Cham. https://doi.org/10.1007/978-3-030-24302-9_19
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