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Enhancing Predictive Maintenance in Operations with Hybrid Analytics

Predictive maintenance is a proactive intervention to ensure the optimal and economical maintenance of equipment while enhancing its net availability for operations. The practice of predictive maintenance requires the development of digital models that will deliver insights based on historical data from measurements, maintenance, and operating conditions. In this webinar, we will discuss the development of models for predictive maintenance by utilizing the synergistic fusion of physics-based models and measurement data from sensors. We will dwell on the following aspects of hybrid-analytics:

  • The need and motiviation of hybrid-analytics
  • Model development with hybrid-analytics
  • Enabling technologies for deployment in real-time digital twins.

We will illustrate these with practical examples.


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