A data analytics and AI-based tool that determines the quality of manufactured products across various application cases based on process parameters, or through inspection.
Servers are available with sufficient computing power to replicate the methodologies established by the Mondragon Unibertsitatea team in different environments. The Mondragon Unibertsitatea team does not include equipment for collecting data in situ, but it is assumed that there are historical process/product data collected in advance. With labeled failures, to perform supervised learning; without known failures, to perform semi-supervised learning (anomalies).
Analysis of specifications, requirements, and feasibility
Demonstrator
Training
Mondragón Goi Eskola Politeknikoa JMA SCoop
Contact person: Urko Zurutuza Ortega
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