Loughborough University
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An intelligent and confident system for automatic surface defect quantification in 3D

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journal contribution
posted on 2015-07-17, 09:06 authored by Mitul Tailor, Jon PetzingJon Petzing, Michael Jackson
Automatic surface defect inspection within mass production of high-precision components is growing in demand and requires better measurement and automated analysis systems. Many manufacturing industries may reject manufactured parts that exhibit even minor defects, because a defect might result in an operational failure at a later stage. Defect quantification (depth, area and volume) is a key element in quality assurance in order to determine the pass or failure criterion of manufactured parts. Existing human visual analysis of surface defects is qualitative and subjective to varying interpretation. Non-contact and three dimensional (3D) analyses should provide a robust and systematic quantitative approach for defect analysis. Various 3D measuring instruments generate point cloud data as an output, although they work on different physical principles. Instrument’s native software processing of point cloud data is often subject to issues of repeatability and may be non-traceable causing significant concern with data confidence. This work reports the development of novel traceable surface defect artefacts produced using the Rockwell hardness test equipment on flat metal plate, and the development of a novel, traceable, repeatable, mathematical solution for automatic defect detection and quantification in 3D. Moreover, in order to build-up the confidence in automatic defect analysis system and generated data, mathematical simulated defect artefacts (soft-artefact) have been created. This is then extended to a surface defect on a piston crown that is measured and quantified using a parallel optical coherence tomography instrument integrated with 6 axis robot. The results show that surface defect quantification using implemented solution is efficient, robust and more repeatable than current alternative approaches.


The authors acknowledge support from the EPSRC Centre for Innovative Manufacturing in Intelligent Automation, in undertaking this research work under grant reference number EP/IO33467/1.



  • Mechanical, Electrical and Manufacturing Engineering

Published in

Key Engineering Materials




46 - 53 (8)


TAILOR, M., PETZING, J.N. and JACKSON, M., 2015. An intelligent and confident system for automatic surface defect quantification in 3D. IN: Fang-Jung, S., Jeng-Ywan, J. and Liang-Kuang, C. (eds). Innovative Technologies in Mechatronics and Robotics, pp. 46 - 53


© Trans Tech Publications Inc


  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date



This is a conference paper. Selected, peer reviewed papers from the 18th International Conference on Mechatronics Technology (ICMT 2014), October 21-24, 2014, Taipei, Taiwan. It was published in the series Key Engineering Materials and the definitive version is available at: http://www.ttp.net/978-3-03835-488-8/toc.html





Book series

Key Engineering Materials;649


  • en