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Data-Driven Methods for PdM in Smart Energies – Hassan Nemati & Kobra Etminani, Halmstad University

Analytics alone will not improve maintenance performance. One needs systematically improve all areas related to proactive maintenance namely process, connectivity, analytics and devices. In Stora Enso we started the transformation journey already some time ago and we have seen good results already.

Key Takeaways

  • In smart grids, large amounts of historical data are available but rarely used for predictive maintenance. Mining and analyzing these historical data can provide valuable information.
  • Applying joint-human machine learning and self-monitoring for detecting faults and errors in district heating using the concept of wisdom of the crowd

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