DNVGL Predictive Maintenance Examples - Jarl S. Magnusson

Presenting the importance of Data Management and Data Quality in order to capture the right data, to adapt (transform and integrate) data and use it for advanced predictive maintenance analytics.

Learning points:

  • Do we underestimate the need for data management and data quality?
  • Profiling and Rules Libraries
  • What is needed for continuous monitoring?
  • Presenting some DNVGL and Customer examples from predictive maintenance

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