This paper aims at describing the key role of Data Quality along the entire development of a Prognostics and Health Management process based on Industrial Artificial Intelligence solutions and ready for industrial application. This is discussed through an industrial case in the textile sector where the importance of Data Quality emerges in different aspects. The industrial case leads to lessons learned useful for further research on a framework for Data Quality in AI-based maintenance systems.

On the role of Data Quality in AI-based Prognostics and Health Management

Cattaneo, L.;Polenghi, A.;Macchi, M.;
2022-01-01

Abstract

This paper aims at describing the key role of Data Quality along the entire development of a Prognostics and Health Management process based on Industrial Artificial Intelligence solutions and ready for industrial application. This is discussed through an industrial case in the textile sector where the importance of Data Quality emerges in different aspects. The industrial case leads to lessons learned useful for further research on a framework for Data Quality in AI-based maintenance systems.
2022
5th IFAC Workshop on Advanced Maintenance Engineering, Services and Technologies, AMEST 2022
Industrial Data Analytics, Industrial Artificial Intelligence, Data Quality, PHM
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1226932
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