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Advisor(s)
Abstract(s)
Nowadays the Industry is becoming increasingly competitive with the emergence of even more advanced technologies. This environment leads the companies to look for a bigger availability of the assets, a higher quality of the products and consequently less costs. Thus, is because of this purpose that Maintenance is becoming even more fundamental. The focus of this paper was to develop a strategy of Predictive Maintenance on a Machine Tool with the aim of reducing the unplanned stops, increasing the productivity and creating the bases for an Industry 4.0 environment in the short term. Thus, a model has been created in order to fulfil this goal. The first step was the selection of the critical component of the machine tool that would be studied. In the next phase the variables that will be monitored were selected and their trigger limits. Finally, the necessary components to monitor this system were chosen. In order to reach the objective, a system of condition-based maintenance where the acoustic emissions and vibration of the bearing of a machine tool were monitor was proposed.
Description
30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021)
15-18 June 2021, Athens, Greece.
Keywords
Machining Machine Tools Maintenance Industry Industry 4.0 Smart Manufacturing Vibration Acoustic Emission Bearing
Citation
Costa, S., Silva, F. J. G., Campilho, R. D. S. G., & Pereira, T. (2020). Guidelines for Machine Tool Sensing and Smart Manufacturing Integration. Procedia Manufacturing, 51, 251-257. DOI 10.1016/j.promfg.2020.10.036
Publisher
Elsevier