In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing

Syam, Wahyudin P. and Leach, Richard K. and Rybalcenko, Konstantin and Gaio, Andrȇ and Crabtree, Joseph (2018) In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing. Procedia CIRP, 75 . pp. 108-113. ISSN 2212-8271

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Abstract

In the last decade, there has been considerable growth in the production of end-use polymer parts and components using additive manufacturing methods. A wide range of polymers, from Nylon-12 to thermoplastic polyurethane polymers, can be processed with complex geometry tailored to specific function. However, due to the nature of the layer-by-layer process used in additive manufacturing, high roughness surfaces remain on the parts. To reduce the roughness of the surfaces, a proprietary post-processing method, developed by Additive Manufacturing Technologies, is applied to the surfaces. To monitor and control the finishing of the surfaces, an in-process surface detection instrument has been developed based on machine vision and machine learning. This paper presents the machine learning approach and the effectiveness of the instrument for in-process measurement of the finished surfaces.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/928806
Additional Information: 15th CIRP Conference on Computer Aided Tolerancing - CIRP CAT 2018. June 11th-13th, Milan, Italy
Keywords: In-process measurement; Additive manufacturing; Machine learning; Machine vision
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
Identification Number: https://doi.org/10.1016/j.procir.2018.04.088
Depositing User: Eprints, Support
Date Deposited: 25 Jun 2018 09:36
Last Modified: 04 May 2020 19:33
URI: http://eprints.nottingham.ac.uk/id/eprint/52583

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