Optimisation of process parameters for dimensional stability in FDM

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Date

2023

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SAGE Publications Ltd

Abstract

The fused deposition modelling (FDM) technique has been adopted in the present work to fabricate Acrylonitrile Butadiene Styrene (ABS) plastic components using input variables like layer thickness, orientation, infill rate and the number of shells. The dimensional geometrical changes of FDM printed built parts, that is, length, width and thickness variation, are optimised individually. Still, a confounding effect is found in the optimisation of individual responses. To overcome this issue, this study uses a fuzzy inference system as an artificially intelligent system. A fuzzy inference system transformed all the responses into one response, known as a multi-response performance index (MPI), and optimised the MPI coupled with Taguchi philosophy. The optimal parameter combination of FDM-printed ABS components for the slightest variation in length, width, and thickness was found to be layer thickness: 200 µm, orientation: 0°, infill rate: 20%,and the number of shells: 3. The significant parametric effect on the responses of FDM components was studied using analysis of variance, and the results reveal that orientation is the most influential parameter trailed by infill rate and the number of shells. © IMechE 2023.

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Keywords

ABS resins, Fused Deposition Modeling, Fuzzy inference, Fuzzy systems, Infill drilling, Intelligent systems, Styrene, Acrylonitrile-butadiene-styrene, Analyse of variance, Artificial smart system, Geometry accuracy, Layer thickness, Multi-response performance index, Multiresponse, Performance indices, Response performance, Smart System, Deposition

Citation

Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2023, , , pp. -

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