Selection of Fused Deposition Modeling Process Parameters Using Finite Element Analysis and Genetic Algorithms
Filip Górski, Radosław Wichniarek, Wiesław Kuczko and Adam Hamrol
The 3D printing technologies have recently found a number of increasing practical applications, despite the fact that the manufacturing processes belonging to this group are still not properly studied and explored. An important problem is lack of methods of prediction of how the process parameters will influence characteristics of a final product, as the influence can be significant, especially in terms of strength. The paper presents a concept of a soft-computing based algorithm of optimization of Fused Deposition Modeling process parameters (FDM is one of the most widespread 3D printing technologies). A core module of this algorithm is a Finite Element Analysis (FEA) performed on digital 3D models resembling structure of a real product and thus named thread models. In the paper, the concept of algorithm is presented in great detail and positive results of studies validating the used FEA approach are shown.
Keywords: Fused deposition modeling, genetic algorithms, finite element analysis, process planning, 3D printing