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Assessment and visualisation of machine tool wear using computer vision

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Abstract

Tool wear monitoring is an integral part of modern CNC machine control. Cutting tools must be periodically checked for possible or actual premature failures, and it is necessary to record the cutting history for a tool’s full life of utilisation. This means that an on-line monitoring system would be of great benefit to overall process control in manufacturing systems. Computer vision has already shown promise as a candidate technology for this task. In this paper, we describe the use of digital image processing techniques in the analysis of images of worn cutting tools in order to assess their degree of wear and thus remaining useful life. It is shown that a processing strategy using a variety of image texture measures allows for effective visualisation and assessment of tool wear, and indicates good correlation with the expected wear characteristics.

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Authors and Affiliations

  1. School of Mechanical and Manufacturing Engineering, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK

    David Kerr, James Pengilley & Robert Garwood

Authors
  1. David Kerr
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  2. James Pengilley
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  3. Robert Garwood
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Correspondence to David Kerr.

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Kerr, D., Pengilley, J. & Garwood, R. Assessment and visualisation of machine tool wear using computer vision. Int J Adv Manuf Technol 28, 781–791 (2006). https://doi.org/10.1007/s00170-004-2420-0

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  • DOI: https://doi.org/10.1007/s00170-004-2420-0

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