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A model enabling proactive maintenance

Taking maintenance work to a new level with machine learning and predictive maintenance systems

How can the company’s own IoT vibration analysis test stand be connected to a cloud and what is the most suitable machine learning model for analysing the sensor data gathered from this? These were the questions XERVON Instandhaltung was hoping to answer when it took part in the ChemTech Hackathon in January. Around 60 IT enthusiasts spent one and half days working together with chemical companies to come up with some ideas and suggestions for innovative tasks.

    • And it was well worth its while: besides providing food for thought and proposing new approaches, it also showed that the predictive maintenance model that XERVON Instandhaltung is looking to develop can indeed be realised. The company’s goal is for it to be used as an early warning system that will enable them to analyse large volumes of data and pick up anomalies at their customers’ plants and so facilitate proactive maintenance.

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