• Media type: E-Article
  • Title: An Industrial Vision System to Analyze the Wear of Cutting Tools
  • Contributor: Gillmann, Christina; Post, Tobias; Kirsch, Benjamin; Wischgoll, Thomas; Hartig, Jörg; Hamann, Bernd; Hagen, Hans; Aurich, Jan Christian
  • Published: Trans Tech Publications, Ltd., 2017
  • Published in: Applied Mechanics and Materials, 869 (2017), Seite 183-194
  • Language: Not determined
  • DOI: 10.4028/www.scientific.net/amm.869.183
  • ISSN: 1662-7482
  • Keywords: General Engineering
  • Origination:
  • Footnote:
  • Description: The wear behavior of cutting tools directly affects the quality of the machined part. The measurement and evaluation of wear is a time consuming and process and is subjective. Therefore, an image-based wear measure that can be computed automatically based on given image series of cutting tools and an objective way to review the resulting wear is presented in this paper. The presented method follows the industrial vision system pipeline where images of cutting tools are used as input which are then transformed through suitable image processing methods to prepare them for the computation of a novel image based wear measure. For multiple cutting tool settings a comparative visualization of the wear measure outputs is presented. The effectiveness of the presented approach is shown by applying the method to measure the wear of four different cutting tool shapes.