Veröffentlichungen

[1]	Barton, D.; Männle, P.; Odendahl, S.; Stautner, M. & Fleischer, J. (2020), „Concept for collision avoidance in machine tools based on geometric simulation and sensor data“. Hrsg. Heizmann, M. & Längle, T., KIT Scientific Publishing, Karlsruhe, S. 171-182. 10.5445/IR/1000126892 Abstract Collisions are a major cause of unplanned downtime in small series manufacturing with machine tools. Existing solutions based on geometric simulation do not cover collisions due to setup errors. Therefore a concept is developed to enable a sensor-based matching of the setup with the simulation, thus detecting discrepancies. Image processing in the spatial and frequency domain is used to compensate for harsh conditions in the machine, including swarf, fluids and suboptimal illumination.
[2]	Barton, D.; Hess, F.; Männle, P.; Odendahl, S.; Stautner, M. & Fleischer, J. (2021), „Image segmentation and robust edge detection for collision avoidance in machine tools“, tm - Technisches Messen, Band 88, Nr. 6, S. 374-385. 10.1515/teme-2021-0028 Abstract Collisions are a major cause of unplanned downtime in small series manufacturing with machine tools. Existing solutions based on geometric simulation do not cover collisions due to setup errors. Therefore a solution is developed to compare camera images of the setup with the simulation, thus detecting discrepancies. The comparison focuses on the product being manufactured (workpiece) and the fixture holding the workpiece, thus the first step consists in segmenting the corresponding region of interest in the image. Subsequently edge detection is applied to the image to extract the relevant contours. Additional processing steps in the spatial and frequency domain are used to alleviate effects of the harsh conditions in the machine, including swarf, fluids and sub-optimal illumination. The comparison of the processed images with the simulation will be presented in a future publication.