Nomad Tech has applied with success Machine Learning to predict upcoming failures in assets on the PMEinCPPS project.
The PMEinCPPS (Predictive Maintenance Experiments in Cyber Physical Production Systems) project was developed in a joint partnership by Nomad Tech and Flowmat as part of the BEinCPPS initiative (project funded by the European Union Framework Programme Horizon 2020) to encourage and nurture the creation of CPS-driven regional innovation ecosystems in Europe. Representing Portugal's Norte Region in this initiative is Fly London's shoe manufacturing company KYAIA.
The tool developed on the PMEinCPPS project is divided in two components:
The tool achieves the predicting capabilities by collecting raw data from a multitude of sensors of the shopfloor factory components, cleaning and transforming it into information interpretable by the end-user that can also be used to train the machine learning models.
The PMEinCPPS tool not only provides predictive maintenance and monitoring capabilities but it also makes use of the BEinCPPS ecosystem big data technologies to make it horizontally scalable and therefore adaptable to different dimensions of data generated by factories cyber physical systems.
PMEinCPPS is an easy to use tool that improves the system availability, reduces the system maintenance costs and helps the end-user to amplify the understanding of how their system really operates on a daily basis.
BEinCPPS project aims to integrate and experiment a Future-Internet-based machine-factory-cloud service platform ﬁrstly intensively in ﬁve selected regions, afterwards extensively in all European regions, bv involving local competence centers and manufacturing SMEs.
More information: http://www.beincpps.eu/