Introducing Hierarchical Particle Swarm Optimization to Optimal Part Orientation in Fused Deposition Modeling Available to Purchase

This article presents hierarchical particle swarm optimization algorithm to determine optimal part orientation for the complex parts produced by fused deposition modeling. Owing to the importance of efficient prototyping during product development phase, it is necessary to address critical issues involved in fused deposition modeling. The best part orientation is explored by taking into account volumetric error, build cost and orientational efficiency in the form of an aggregate objective. This paper exploits the search efficiency exhibited by hierarchical particle swarm optimization (HPSO), an optimization algorithm working on the basis of swarm intelligence, with the aim to resolve underlying optimal part orientation (OPO) problem. Further, in order to establish efficacy of HPSO a comparative study has been performed with a genetic algorithm based search. The results indicate outperforming behavior of HPSO and thus it is claimed to be a viable and efficient alternative to OPO problem.