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Jhennifer F. dos Santos
Faculdade de Engenharia Elétrica e Biomédica, Universidade Federal do Pará (UFPA), Belém
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Lucas H. B. Santos
Faculdade de Engenharia Elétrica e Biomédica, Universidade Federal do Pará (UFPA), Belém
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Wellington da S. Fonseca
Programa de Pós-Graduação em Engenharia Elétrica (PPGEE), UFPA
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Allan R. A. Manito****
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Ramon C. F. Araujo
Programa de Pós-Graduação em Engenharia Mecânica (PPGEM), UFPA, Belém
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Marcelo de O. e Silva
Programa de Pós-Graduação em Engenharia Mecânica (PPGEM), UFPA, Belém
Keywords:
IIoT, Reliability, Predictive maintenance, Online dashboard, ESP32
Abstract
A with the advancement of technology within the manufacturing area and an increase in the production process, the industry increasingly needs means that allow reliability in their manufacturing methodology. Thus, the Industrial Internet of Things (IIoT) becomes a new tool adopted in this environment, since this technology allows the connection of sensors with web databases to monitor the equipment present in the industry. As a consequence of this connectivity, a greater excellence in predictive maintenance applicability is possible, since IIoT technologies allow the visualization of monitored parameters in real time. Thus, this paper demonstrates the Motor Monitoring and Analysis System (SMAM) that measures temperature and three-phase motor input current with low cost devices, allowing the user to monitor these variables in an online dashboard.