7. Technologies and data used in predictive maintenance
Since the 1950s, the technologies used for predictive maintenance have evolved with industry. In Industry 3.0, they relied on simple wired sensors and static thresholds based on classical models. Industry 4.0 introduced IoT, AI and cloud computing, enabling real-time data collection and adaptive predictive models. For almost a decade, Industry 5.0 has been taking up these technologies, putting people at the center of decision-making, with a resilient and sustainable approach. This section presents the characteristics of smart sensors and IoT, as well as an inventory of sensors and key data for predictive maintenance.
7.1 Classic sensors
The classic sensors of Industry 3.0, the third industrial revolution marked by automation via electronics and IT, are designed...
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Technologies and data used in predictive maintenance
Limitations of RUL estimation methods
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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