8. Limitations of RUL estimation methods
The accuracy of remaining useful life (RUL) estimates and probabilistic failure predictions depends on a number of determining factors relating to the data, the methods used and the operating context. Firstly, data quality plays a fundamental role in the reliability of predictions. Secondly, modeling and the choice of algorithms directly influence the accuracy of estimates. The adoption of physical, statistical or artificial intelligence-based models must be adapted to the volume and diversity of the data available. Machine learning approaches, although powerful, require a representative learning base to avoid bias and guarantee reliable predictions.
Furthermore, the temporal evolution of systems requires regular updating of models to avoid obsolescence. On-line learning enables predictions to be adjusted in line with new data and changing operating conditions....
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Limitations of RUL estimation methods
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Bibliography
Websites
Site on company classification according to the French Ministry of the Economy and Finance
European Commission website on Industry 5.0
https://commission.europa.eu/index_en
Safran...
Standards and norms
- System reliability analysis techniques – Procedure for analyzing failure modes and their effects (FMEA). - IEC – NF EN 60812 - 2006
- Functional safety of safety-related electrical/electronic/programmable electronic systems – Part 1: General requirements. - CEI 61508-1 - 2010
- Procedures for performing a failure mode, effects, and criticality analysis. - MIL-P-1629 - 9 nov. 1949
- Analysis techniques...
Directory
Organizations – Federations – Associations (non-exhaustive list)
AFNOR: Association française de normalisation
https://normalisation.afnor.org/
AFIM: French Association of Maintenance Engineers
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