Incident Management and Predictive Maintenance

Improve the reliability of your green energy assets using Artificial Intelligence (AI) and decrease energy production downtime and O&M costs

Use Aqovia A1 Autonomic Platform artificial intelligence (AI) algorithms to manage your green energy generation assets. This will give you optimum performance by improving your ability to intelligently control your incident management and improve your predictive maintenance regime.

Incident Management

Asset owners and operators complain about the number of false-positive alarms generated by their green energy assets.

Control room operators receive many more alarms in their working shifts than the recommended 1 alarm every 5 minutes.

This reduces operator effectiveness as it prevents control room operators from being able to clearly differentiate between actual alarms and false positives.

Get a copy of our incident management case study

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Predictive Maintenance

Unscheduled maintenance corrodes your margins and makes profitability unpredictable..

Up to 50% of all green energy costs can be attributed to maintenance and it quickly becomes clear that there are significant margin gains to be recovered by better planning of maintenance. In addition to this, there is, obviously, also a significant Health and Safety gain to be made by reducing the number of times your staff need to visit remote and difficult to reach sites.

Get a copy of our predictive maintenance case study

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The benefits

  1. 95% reduction in the number of alarms received by the NOC
  2. 70% reduction in false positive alarms dealt with by the NOC
  3. 40% reduction in the incident-to-resolution path
  4. 50% reduction in unplanned site visits
  5. 50% potential reduction in maintenance costs

Want to know more about Aqovia's Artificial Intelligence platform?

  • A1 Autonomic Platform

    Introducing an automated and intelligent platform for streamlined operations, cost reduction and experience uplift.

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