Experimental Investigations and Multi-Objective Optimization of Selective Inhibition Sintering Process Using the Dragonfly Algorithm

Abstract

The chapter focuses on utilizing a hybrid approach of response surface methodology and dragonfly algorithm for investigations and optimization of the selective inhibition sintering (SIS) process to improve the mechanical strengths such as tensile and flexural of fabricated high density polyethylene parts. The layer thickness (LT), heater energy (HE), heater and printer feedrate (HFR & PFR) are considered as the independent variables for the investigation. The SIS experiments are planned and conducted through a response surface methodology-based box-Behnken design approach to fabricate the test specimens. The optimal SIS parameters are obtained through a swarm intelligence metaheuristic technique namely dragonfly algorithm (DFA). The optimal parameter settings of LT of 0.102 mm, HE of 28.46 J/mm2, HFR of 3.22 mm/sec, and PFR of 110.49 mm/min are achieved through DFA for improved tensile and flexural strengths of 26.21 MPa and 65.71 MPa, respectively. Further, the prediction ability of DFA was compared with particle swarm optimization algorithm.