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On the role of data quality in AI-based prognostics and health management
Conference proceeding   Peer reviewed

On the role of data quality in AI-based prognostics and health management

Laura Cattaneo, Adalberto Polenghi, Marco Macchi and Valerio Pesenti
IFAC-PapersOnLine, Vol.55(19), pp.61-66
5th IFAC workshop on advanced maintenance engineering, services and technologies AMEST 2022 (Bogotà, Colombia, 26/07/2022 - 29/07/2022)
2022
Scopus ID: 2-s2.0-85142222937
DOI: https://doi.org/10.1016/j.ifacol.2022.09.184
Web of Science ID: WOS:000860839700011

Abstract

Automation & control systems Science & technology Industrial data analytics Industrial artificial intelligence Data quality PHM Technology
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.
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https://doi.org/10.1016/j.ifacol.2022.09.184View
Published (Version of record)CC BY-NC-ND V4.0,  Open

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