Predictive
Maintenance

EXPLORE-AI's Predictive Maintenance solutions help operators to understand assets' maintenance schedules, how to optimise asset spend and ultimately improve customer satisfaction.

Large networks break. Often. More often than we would like. Our large utility networks are sometimes old, stretched across thousands of miles of countryside, exposed to extreme weather, vandalism and poor workmanship. So things do go wrong on a regular basis.

When they break it is a problem. Customers become unhappy when critical services are interrupted. Regulators also become distressed when these services aren’t working perfectly. So to be able to predict which assets to fix when, is a very valuable skill.

EXPLORE has worked with large utility networks to build out predictive maintenance programmes to minimise any interruptions. We are able to:

  • See what assets have broken when with what frequency over time
  • Understand the full cost of these issues
  • Build algorithms to predict the interruptions into the future
  • Build investment models that value various maintenance schedules
  • Prepare a prescriptive long term maintenance schedule to optimise network performance
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