Abstract
Currently, only two direct automatic tool damage detection systems are available in the tool resharpening industries of German market. Both systems work on the principle of laser-optical 3D detection. By means of non-contact laser scanning, 3D models of the scan object are created which are then compared with digitally stored original model of the tools through a software. Damage images are created based on detected deviations. However, these systems have the major decisive disadvantage that they require about 15 to 20 min for a complete detection of a tool and are quite expensive, ranging between 100,000–400,000 Euros. Therefore, there is a scope of technically and economically optimized tool quality inspection system. The main goal of this work is to develop a new method by which the damages of different coated tools are identified with reduced cost and without compromising the accuracy of the damage.
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Bilal, M., Mayer, C., Kancharana, S., Bregulla, M., Cupek, R., Ziebinski, A. (2022). Damage Detection of Coated Milling Tools Using Images Captured by Cylindrical Shaped Enclosure Measurement Setup. In: Bădică, C., Treur, J., Benslimane, D., Hnatkowska, B., Krótkiewicz, M. (eds) Advances in Computational Collective Intelligence. ICCCI 2022. Communications in Computer and Information Science, vol 1653. Springer, Cham. https://doi.org/10.1007/978-3-031-16210-7_21
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