MANUELA | Additive Manufacturing using Metal Pilot Line
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The Battery Pilot will aim at demonstrating that the DigiPrime platform can unlock a sustainable business case targeting the remanufacturing and re-use of second life Li-Ion battery cells with a cross-sectorial approach linking the e-mobility sector and the renewable energy sector, specifically focusing on solar and wind energy applications.
As the proactive exploitation of the DigiPrime platform enables the car-monitored SOH tracing and availability, less testing is needed to assess the residual capacity of the battery. Moreover, by knowing the structure of the battery packs, a decision support system can be implemented to adjust the de-and remanufacturing strategy accordingly and select the most proper cells for re-assembly second-life modules, thus unlocking a systematic circular value chain for Li-ion battery cells re-use. Furthermore, excessively degraded cells which cannot be re-used can be sent to high-value recycling, based on the knowledge of their material compositions.
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Main challenges identified are:
Training the existing workforce to use the new technologies is identified as a main challenge
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PROGRAMS aims at developing a HW/SW suite of solutions capable of:
PROGRAMS solution will allow SMEs to access the benefits of Predicitive Maintenance wilth limited costs.
Several challenges limit the succesfull application of Predictive Maintenance in factories:
Correct determination of best maintenance strategies and computation of components RUL requires the collection of a vast amount of data in a format that must be easily accessible and analyzed.
Robot components show a slow degradation of their performances: data collection must begin as soon as possible.
Predictive maintenance requires different skills and thus new professional figures will have to to be trained:
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GESTAMP, besides getting familiar with Z-BRE4K’s solution validation and assessment methodology, got a better understanding of internal reflection and readiness to apply predictive maintenance solutions to its plants while new mitigation actions related to process flaws and defects identification were developed during the Z-BRE4K. Also, they have understood the importance of solution validation and assessment methodology defined in Z-BRE4K.
PHILIPS supports the idea of predictive maintenance, “listening to the machines” and understands that the key to success is close contact between technology providers and experts where data integration/architecture and machine learning are both very important projects.
SACMI-CDS found out the importance of collaboration not only with a mechanical engineering/maintenance-related professionals but also with different technical background experts that together can improve multi-tasking and combining shopfloor and office-related activities as well as scheduling of activities during the work journey.
In general, after the solution implementation (TRL5), testing the system on the shop floor (TRL6) and validation of the Z-BRE4K solution (TRL7) at end users, the very final lesson learnt can be summarised as follows:
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Benefits: