Abstract
Manufacturing process monitoring is showing great advances thanks to increasing sensor availability and the development of edge to cloud IoT systems. However, the application of this technology in industry is slowed down due to cyber security policies, the coexistence of old manufacturing systems, with limited monitoring capabilities, with newer and fully monitored ones, and the lack of application-oriented functionalities. In this paper, a fast and automated machine tool characterization procedure, called Fingerprint, is presented, that allows determining useful Key Performance Indicators of the status of machine tools based on IoT technologies. The paper also presents the implementation of this technology in industrial environment.
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CITATION STYLE
Armendia, M., San Sebastian, J., Gonzalez, D., Santamaria, B., Gonzalez, J. A., Gonzalez-Velazquez, R., & Lopez de Calle, K. (2021). Fingerprint: Machine tool condition monitoring approach for zero defect manufacturing. MM Science Journal, 2021-November, 5247–5253. https://doi.org/10.17973/MMSJ.2021_11_2021159
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