Additive manufacturing : Optimization of process parameters for fused filament fabrication

Abstract: An obstacle to the wide spread use of additive manufacturing (AM) is the difficulty in estimating the effects of process parameters on the mechanical properties of the manufactured part. The complex relationship between the geometry, parameters and mechanical properties makes it impractical to derive an analytical relationship and calls for the use of a numerical model. An approach to formulate a numerical model in developed in this thesis. The AM technique focused in this thesis is fused filament fabrication (FFF). A numerical model is developed by recreating FFF build process in a simulation environment. Machine instructions generated by a slicer to build a part is used to create a numerical model. The model acts as a basis to determine the effects of process parameters on the stiffness and the strength of a part. Determining the stiffness of the part is done by calculating the response of the model to a uniformly distributed load. The strength of the part depends on it's thermal history. The developed numerical model serves as a basis to implement models describing the relation between thermal history and strength. The developed model is suited to optimize FFF parameters as it encompass effects of all FFF parameters. A genetic algorithm is used to optimize the FFF parameters for minimum weight with a minimum stiffness constraint.