Detalhes bibliográficos
| Resumo: | The present paper describes the state of the art related to IIoT Devices and Cyber-Physical systems and presents a use case related to predictive maintenance. Industry 4.0 is the boost for smart manufacturing and demands flexibility and adaptability of all devices/machines in the shop floor. The machines must become smart and interact with other machines inside and outside the industries/factories. The predictive maintenance is a key topic in this industrial revolution. The reason is based on the idea that smart machines must be capable to automatically identify and predict possible faults and actuate before they occur. Vibrations can be problematic in electrical motors. For this reason, we address an experimental study associated with an automatic classification procedure, that runs in the smart devices to detect anomalies. The results corroborate the applicability and usefulness of this machine learning algorithm to predict vibration faults. |
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| Autores principais: | Rubio, Eva Masero |
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| Outros Autores: | Dionísio, Rogério Pais; Torres, Pedro |
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| Assunto: | Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
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| Ano: | 2019 |
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| País: | Portugal |
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| Tipo de documento: | capítulo de livro |
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| Tipo de acesso: | acesso aberto |
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| Instituição associada: | Instituto Politécnico de Castelo Branco |
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| Idioma: | inglês |
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| Origem: | Repositório Científico do Instituto Politécnico de Castelo Branco |
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