How an electric company applies predictive analytics

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Israel Electric Corporation is responsible for generating 95% of the country’s electricity. To meet peak demand, its turbines need to run at full capacity, making reliability and efficiency absolutely vital.

This use case describes how IEC utilizes IBM’s predictive analytics software to model the behavior of its turbines and monitor their performance in real time. When anomalies are detected, it quickly triggers maintenance resources to fix problems before outages occur. Read on to learn the major benefits that IEC has experienced, including:

  • Cost savings of nearly $75,000 per turbine by identifying inefficient fuel usage
  • A 20% reduction in costs by avoiding the need to restart turbines following an outage
  • Early warnings of failure are received up to 30 hours before they occur instead of 30 minutes
  • And more
Feb 8, 2021
Sep 30, 2013
Case Study
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