Optimization of significant factors for improving compressive strength of ABS in Fused Deposition Modeling by using GA & RSM

Abstract

The current research work is focused on optimization of FDM 3D printer input factors for compressive strength of ABS fabricated parts. It is a carbon chain copolymer thermoplastic possessing high impact strength and rigidity. Response Surface Methodology (RSM) and Genetic algorithm (GA) integrated with each other to optimize the input factors. Five factors viz. Layer thickness (LT), Build Orientation (BO), Raster angle (RA), Raster width (RW) and Air gap (AG) have been studied and modeled for compressive strength utilizing RSM. In present experimentation, quadratic model has been suggested for compressive strength. Build Orientation is most significant factor that imparts considerable effect on compressive strength as compared to other factors. Finally, GA-RSM, a popular hybrid evolutionary approach is used to optimize the factors.