Optimization of FDM Printing Process Parameters on Surface Finish, Thickness, and Outer Dimension with ABS Polymer Specimens Using Taguchi Orthogonal Array and Genetic Algorithms

Jasgurpreet Singh Chohan, Raman Kumar, Aniket Yadav, Piyush Chauhan, Sandeep Singh, Shubham Sharma, Changhe Li, Shashi Prakash Dwivedi, S. Rajkumar and Jiafu Su

Mathematical Problems in Engineering, 2022, vol. 2022, 1-13

Abstract: Fused deposition modelling (FDM) is a technique of additive manufacturing used to fabricate a 3D (three-dimensional) model with layer-by-layer deposition of required materials with less material wastage. FDM is used to make any objects with a meager cost, but also there are some negative points related to less strength, less accuracy, and less surface finish. In this study, acrylonitrile butadiene styrene (ABS) is printed using an FDM printer to investigate the effects of various changing parameters like nozzle temperature (°C), infill pattern, and printing speed (mm/s) on surface roughness and thickness measurement. Experiments are designed using the Taguchi L9 orthogonal array method and ANOVA method. For obtaining an increase in surface roughness, the most influencing factor is printing speed with 83.41% contribution, and the effect of nozzle temperature is 9.04%. Lesser printing speed enhances the surface finish and, in the case of thickness and outer dimension of all the printed samples, results are almost constant. Regression analysis is performed to formulate the single-objective equations, and a genetic algorithm (GA) is applied to optimize the values of process parameters.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:2698845

DOI: 10.1155/2022/2698845

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