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Multi-Objective Optimization of Additive Manufacturing Process

IFAC-PapersOnLine 2018年第11期51卷 152-157页

作者： Asadollahi-Yazdi, Elnaz Gardan, Julien Lafon, Pascal ICD/LASMIS UMR CNRS 6281 University of Technology of Troyes Troyes France EPF Engineering school Rosière-Près-Troyes France

This paper presents an approach to analyze the critical drawbacks and attributes of Additive Manufacturing (AM) simultaneously to find the best manufacturing parameters to fabricate the AM products. In this study, Fused Deposition Modeling (FDM) is investigated as a common AM technology. For this purpose, a multi-optimization problem is formulated according to the analysis of FDM technology. In this problem, layer thickness and part orientation are determined as the decision variables which are the important parameters of manufacturing. As objective functions, production time and material mass are considered and the surface roughness of FDM products and mechanical behavior of material are defined as the constraint functions. Different methodologies are developed to model the AM criteria according to these decision variables. To find the optimal solutions for manufacturing, Non-dominated sorting genetic algorithm-II (NSGA-II) is used. Finally, a case study highlighted the reliability of the proposed approach. © 2018

关键词： Multiobjective optimization 3D printers Decision making Deposition genetic algorithms Layered manufacturing Stochastic systems Surface roughness Additive manufacturing process Fused deposition modeling Manufacturing parameters Mechanical behavior of materials Multi objective optimization problem Non dominated sorting genetic algorithm ii (NSGA II) Non dominated sorting genetic algorithm ii Stochastic algorithms

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