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Tool-Wear Analysis Using Image Processing of the Tool Flank
1
Department of Mechatronics, University of Oradea, 410087 Oradea, Romania
2
Department of Energy Engineering, University of Oradea, 410087 Oradea, Romania
3
Department of Mathematics—Computer Science, Aurel Vlaicu University of Arad, 310025 Arad, Romania
4
Department of Social Sciences, Agora University, 410526 Oradea, Romania
*
Author to whom correspondence should be addressed.
†
Current address: Department of Mathematics—Computer Science, Aurel Vlaicu University of Arad, 310025 Arad, Romania.
‡
These authors contributed equally to this work.
Symmetry 2017, 9(12), 296; https://doi.org/10.3390/sym9120296
Received: 5 November 2017 / Revised: 27 November 2017 / Accepted: 28 November 2017 / Published: 30 November 2017
(This article belongs to the Special Issue Civil Engineering and Symmetry)
Flexibility of manufacturing systems is an essential factor in maintaining the competitiveness of industrial production. Flexibility can be defined in several ways and according to several factors, but in order to obtain adequate results in implementing a flexible manufacturing system able to compete on the market, a high level of autonomy (free of human intervention) of the manufacturing system must be achieved. There are many factors that can disturb the production process and reduce the autonomy of the system, because of the need of human intervention to overcome these disturbances. One of these factors is tool wear. The aim of this paper is to present an experimental study on the possibility to determine the state of tool wear in a flexible manufacturing cell environment, using image acquisition and processing methods.
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Keywords:
image processing; flexible manufacturing; tool-flank-wear monitoring; artificial neural networks
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MDPI and ACS Style
Moldovan, O.G.; Dzitac, S.; Moga, I.; Vesselenyi, T.; Dzitac, I. Tool-Wear Analysis Using Image Processing of the Tool Flank. Symmetry 2017, 9, 296.
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