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

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  • Vimal Kumar Pathak

    (Malaviya National Institute of Technology, Jaipur, India)

  • Amit Kumar Singh

    (Malaviya National Institute of Technology, Jaipur, India)

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.

Suggested Citation

  • Vimal Kumar Pathak & Amit Kumar Singh, 2017. "A Particle Swarm Optimization Approach for Minimizing GD&T Error in Additive Manufactured Parts: PSO Based GD&T Minimization," International Journal of Manufacturing, Materials, and Mechanical Engineering (IJMMME), IGI Global, vol. 7(3), pages 69-80, July.
    • Handle: RePEc:igg:jmmme0:v:7:y:2017:i:3:p:69-80
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