machine learning

2 min

Predictive maintenance with artificial intelligence

Renewable energy is one of the key assets in the modern world, making wind and photovoltaic plants efficient is therefore becoming critical to the success of not only the producing companies but also consumers and the environment itself.

How can plants be monitored and kept in optimal condition? Artificial intelligence becomes the right ally. Let’s find out how.

What predictive maintenance means

Predictive maintenance represents an intervention methodology with regularly scheduled activities to avoid unexpected failures. This type of maintenance involves the identification, and subsequent monitoring, of specific parameters thus managing to maintain equipment, computers and industrial machinery in optimal operating conditions, avoiding failures and, above all, machine downtime and therefore interruption of production.

With Artificial Intelligence, maintenance becomes even more effective. In fact, as time passes and data accumulates, the algorithms improve their knowledge of the plants and learn to give increasingly accurate alerts with greater notice. This leads to greater effectiveness and productivity of the plant itself, and also allows faults to be detected in a timely manner by facilitating their interpretation and correction.

The advantages of predictive maintenance

What happens when predictive maintenance with AI is applied in photovoltaic and wind power plants? There are multiple advantages:

  • performance monitoring;
  • increased effectiveness and productivity with the use of AI tools;
  • failure prevention;
  • optimization of maintenance costs;
  • reduced downtime;
  • increased asset life;
  • work planning;
  • reduction of technical interventions and accident risks.

To take full advantage of the advantages of predictive maintenance on renewable plant, three conditions must be met:

  • real-time (SCADA) data on the condition of various components and failures must be available;
  • It is necessary to schedule downtime at times convenient to production;
  • It is necessary to plan for the procurement of spare parts and required staff in good time.

At Omninext, our highly specialized teams offer innovative digital solutions both in the energy and environmental fields and in the area of Artificial Intelligence with Machine Learning. We also elaborate cross-cutting solutions such as projects useful for predictive maintenance with Artificial Intelligence. Contact us for a consultation!

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