Nomad Tech applies Predictive Analytics in Asset Maintenance

Monday, 16th October 2017

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 STATSFLY component provides a real time monitoring tool of the shop floor status. Furthermore it allows the user to analyse the historical states of the shopfloor, the status of each component, statistical data, the historical failures log and the reasons why they occurred.
  • The PREDITAIN component uses machine learning techniques to create a predictive maintenance model that pre-emptively detects degradation related failures in the factory components before they occur.

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.


About BEinCPPS:

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.

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