Proceedings of the
9th International Conference of Asian Society for Precision Engineering and Nanotechnology (ASPEN2022)
15 – 18 November 2022, Singapore

An Analysis and Optimization of Surface Quality in Post-processing of 3D Printed Surfaces Using Fluid Jet Polishing

Lai Ting Ho1,a, Chi Fai Cheung1, Ruoxin Wang1, Yee Man Loh1, Chunjin Wang1 and Tsz Chun Lai1

1State Key Laboratory of Ultra-precision Machining Technology, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, HKSAR, China


Surface defects including Pores, cracks and unmetled powder are commonly found on the surface of most 3D-printed components. This paper attempts to analyse the effect of fluid jet polishing on surface quality after post-process finishing of 3D-printed surfaces. In this paper, the surface defects before and after post-process finishing of the 3D-printed surfaces by FJP were investigated first. The surfaces were then measured while the types and number of defects captured before and after polishing were determined and analyzed by a purpose-built machine-learning algorithm which was built based convolutional neural network. Hence, post-polishing process parameters was optimized by Taguchi Method. The results of the study will gain better scientific understanding of the effectiveness of postprocessing by FJP but also further enhance the surface quality of 3D-printed components.

Keywords: Neural network, Fluid jet Polishing, Optimization,3D-printing

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