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Reducing bearing defects with predictive analytics

Within STREAM-0D solution, Data-Driven Models (DDMs) represent a crucial element to predict potential product defects; CETRI’s work is dedicated to the definition of DDMs. This article describes the tests carried out on Fersa Bearings line.

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Detecting defects in brake boosters with machine learning

CETRI, that in STREAM-0D is in charge of data fusion, data sparsification and data-driven models, works closely with end-users to reduce the variability in the context of product performance so to better meet the requirements for suppliers.

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