The mechanical properties of parts built with material extrusion additive manufacturing are highly dependent on the material distribution within parts’ microstructure. This varies with the choice of process parameters. Therefore, when designing a functional printed part, one must tailor the printing parameters in order to obtain the desired properties, such as minimal voids. The present work proposes an optimisation method that designs printing parameters to minimize manufacturing time while keeping the void volume fraction at very low values (hence improving mechanical properties), keeping dimensions within tight tolerances and guaranteeing structural integrity. The new optimisation method utilises the authors’ previously developed software VOLCO-X, which is capable of efficiently predicting H#11.1 material distribution from filament extrusion within printed parts, including print track dimensions and microstructure geometry, without the need for any experimental calibration. In order to validate the proposed optimisation scheme, optimised printed parts using the scheme and parts using printing parameters determined by a commercial slicing software were manufactured and compared for different printing speeds and deposition strategies. H#4.1 At printing speed of 16 mm/s, it was possible to decrease the manufacturing time by more than 20% and structural mass by more than 5% in comparison to the commercial slicer printed part, whilst maintaining similar mechanical properties. H#4.2 At printing speed of 96 mm/s, due to the high printing speed, the commercial printed part presented gap faults between deposited strands, while the optimised part had structural integrity. At this printing speed, the optimised printed part presented significant improvements in terms of mechanical properties. The proposed optimisation methodology, in conjunction with VOLCO-X, is a powerful tool that can be used to improve manufacturing H#11.2 by filament extrusion. This innovative tool allows the identification of printing parameters without experiments and trial-and-error approaches, thus saving time and expense.