Large Scale Predictive Maintenance for Leading German Car Manufacturer


Achievement

  • Project realization: 3 years
  • Savings: 17.5 million Euro yearly
  • Implementation of 17 predictive maintenance use cases

Summary

Development of predictive maintenance solution for seventeen production use-cases: connecting production PLC’s delivering business intelligence insights by using big data, machine learning, deep learning and software development. Improvement of the production line efficiency by 2 percent yielding multi-million Euros in savings.

 


Technology Used

  • Azure IoT Hub
  • OPC UA
  • Azure Stream Analytics and Eventhub
  • Azure Functions and Spark Databricks
  • Azure Cosmosdb and Microsoft SQL Server
  • Azure Data Lake and Blob Storage
  • Tensorflow/ Scikit Learn
  • Microsoft PowerBI
  • R, Python, PHP, Bootstrap