Semi-Double-loop machine learning based CPS approach for predictive maintenance in manufacturing system based on machine status indications
The paper presents two original and innovative contributions: 1) the model of machine learning (ML) based approach for predictive maintenance in manufacturing system based on machine status indications only, and 2) semi-Double-loop machine learning based intelligent Cyber-Physical System (I-CPS) arc...
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| Outros Autores: | , , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2021
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| Assuntos: | |
| Texto completo: | https://hdl.handle.net/1822/77995 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/77995 |
| Resumo: | The paper presents two original and innovative contributions: 1) the model of machine learning (ML) based approach for predictive maintenance in manufacturing system based on machine status indications only, and 2) semi-Double-loop machine learning based intelligent Cyber-Physical System (I-CPS) architecture as a higher-level environment for ML based predictive maintenance execution. Considering only the machine status information provides rapid and very low investment-based implementation of an advanced predictive maintenance paradigm, especially important for SMEs. The model is validated in real-life situations, exploring different learning algorithms and strategies for learning maintenance predictive models. The findings show very high level of prediction accuracy. |
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