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GE Digital

Industrial AI

Machine Learning and Analytics: Process Engineers Don’t Have to Be Data Scientists

50 mins

Speakers

  • Cobus van Heerden

    Cobus van Heerden

    Senior Product Manager, Analytics and Machine Learning

    GE Digital

Video details

Watch this webinar to learn the proven processes and software technologies that make analytics do-able for every industrial organization.

Today, staying competitive means progressing with machine learning and analytics. Fortunately, the journey to success doesn’t require that process engineers need to be data scientists.

You’ll learn how to align engineering domain expertise to five capabilities:

  1. Analysis - automatic root cause identification accelerates continuous improvement
  2. Monitoring – early warnings reduce downtime and waste
  3. Prediction – proactive actions improve quality, stability, and reliability
  4. Simulation – what-if simulations accelerate accurate decisions at a lower cost
  5. Optimization – optimal process setpoints improve throughput at acceptable quality by up to 10%

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