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

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.

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Selection of optimal part orientation in fused deposition modelling using swarm intelligence

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1243/09544054jem771 ◽

2007 ◽

Vol 221 (7) ◽

pp. 1209-1219 ◽

Cited By ~ 23

Author(s):

A Ghorpade ◽

K P Karunakaran ◽

M K Tiwari

Keyword(s):

Particle Swarm Optimization ◽

Swarm Intelligence ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Particle Swarm ◽

Fused Deposition Modelling ◽

Swarm Optimization ◽

Part Quality ◽

Fused Deposition ◽

Part Orientation

This paper presents a swarm intelligence approach for optimal orientation of a part produced by the fused deposition modelling method, with a view to reduce the volumetric errors that are primarily responsible for poor surface finish. A part is oriented in such a way to assist the designer in reducing build time, while at the same time enhancing part quality and orientational efficiency. The conventional approach in optimization of part orientation considers only minimization of the staircase effect in order to enhance the part quality. In the approach used by the present authors, a part is oriented by transforming it about x and y axes and an orientation is selected that not only provides minimum volumetric error and building time but also enhances orientational efficiency of the fused deposition modelling method. Using the swarm intelligence technique, the hierarchical particle swarm optimization algorithm is employed to obtain optimal part orientation. The results obtained by using the hierarchical particle swarm optimization algorithm are further compared with the results obtained by using the genetic algorithm; the results reveal that the hierarchical particle swarm optimization algorithm provides a better outcome than the genetic algorithm. An example is given to illustrate the approach.

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