Genetic algorithm for the reduction printing time and dimensional precision improvement on 3D components printed by Fused Filament Fabrication

Abstract

Additive manufacturing (AM) has managed to stand out globally, with a financial forecast growth of $26.28 billion by 2027, where $14.54 billion will be generated due to fused filament fabrication (FFF) technology. Despite this significant growth, researchers in the FFF field are working on solving problems associated with productivity and efficiency, where finishing components are one of the most critical aspects. This paper reports the implementation of a genetic algorithm (GA) to optimize the extruder path during the FFF process, comparing the results based on the dimensional finish of a printed component with the traditional method (CTRAD) with a printed component with the implementation of a GA that modifies the 3D printing path (CMOD). The methodology includes (1) FFF of the CTRAD and FFF of the CMOD and (2) measuring and comparing 118 dimensions associated with each attribute of CTRAD and CMOD using a coordinate measuring machine (CMM). Comparisons are made among the computer-aided design (CAD), the CTRAD, and the CMOD. Results show that 83.9% of the dimensions of the CTRAD components are different from the dimensions of the components defined in the CAD, and 81% of the dimensions of the CMOD components are different from the dimensions of the components defined in the CAD. Finally, 53% of the dimensions in the CTRAD are different from those in the CMOD. The implementation of the GA helps reduce the lead time of the subject of study by 11.2%, ensuring that the surface texture of CTRAD and CMOD has the same behavior and is greater than those defined in CAD design. Also, it is identified that there is no significant dimensional difference between the CTRAD and the CMOD.