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A Particle Swarm Optimization Approach for Minimizing GD&T Error in Additive Manufactured Parts: PSO Based GD&T Minimization

A Particle Swarm Optimization Approach for Minimizing GD&T Error in Additive Manufactured Parts: PSO Based GD&T Minimization
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Author(s): Vimal Kumar Pathak (Malaviya National Institute of Technology, India) and Amit Kumar Singh (Malaviya National Institute of Technology, India)
Copyright: 2020
Pages: 13
Source title: Additive Manufacturing: Breakthroughs in Research and Practice
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-9624-0.ch008

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Abstract

This paper presents a particle swarm optimization (PSO) approach to improve the geometrical accuracy of additive manufacturing (AM) parts by minimizing geometrical dimensioning and tolerancing (GD&T) error. Four AM process parameters viz. Bed temperature, nozzle temperature, Infill, layer thickness are taken as input while circularity and flatness error in ABS part are taken as response. A mathematical model is developed for circularity and flatness error individually using regression technique in terms of process parameters as design variables. For the optimum search of the AM process parameter values, minimization of circularity and flatness are formulated as multi-objective, multi-variable optimization problem which is optimized using particle swarm optimization (PSO) algorithm and hence improving the geometrical accuracy of the ABS part.

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