UPTIME will seek to reframe predictive maintenance strategy by proposing a unified framework and to create an associated unified information system in alignment to the aforementioned framework. Therefore, UPTIME will extend and unify new digital, e-maintenance services and tools in order to exploit the full potential of a predictive maintenance strategy with the UPTIME solution, will deploy and validate the UPTIME solution in the manufacturing companies participating in the UPTIME consortium and will diffuse the UPTIME solution in the manufacturing community.
UPTIME will enable manufacturing companies having installed sensors to fully exploit the availability of huge amounts of data with respect to the implementation of a predictive maintenance strategy. Moreover, production, quality and logistics operations driven by predictive maintenance will benefit from UPTIME. UPTIME will enable manufacturing companies to reach Gartner’s level 4 of data analytics maturity (“optimized decision-making”) in order to improve physically-based models and to synchronise maintenance with quality management, production planning and logistics options. In this way, it will optimize in-service efficiency through reduced failure rates and downtime due to repair, unplanned plant/production system outages and extension of component life. Moreover, it will contribute to increased accident mitigation capability since it will be able to avoid crucial breakdown with significant consequences.
Consequently, UPTIME will exploit the full potential of predictive maintenance management and its interactions with other industrial operations by investigating a unified methodology and by implementing a unified information system addressing the predictive maintenance strategy.
Field of science
- /social sciences/sociology/governance/public services
- /social sciences/economics and business/economics/production economics
- /natural sciences/computer and information sciences/data science/data analysis
Call for proposal
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Funding SchemeIA - Innovation action