Recommender systems are applications of data mining that deal significantly with the information overload problem. Systems like these have had a huge impact on other industries such as e-commerce and video streaming, leaders in this area such as Amazon and Netflix, have changed the way they interact in their respective businesses; it has brought many advantages to theme. We Apply this successful idea to a new context. For instance, in the process of asset management decision. At Interconexión Eléctrica S.A (ISA) one of the largest transporter of electricity in Latin America has successfully developed a recommender system to support the decision of maintenance activities on power transformers, based on the history of maintenance activities and the failure mode of the equipments.

Session Takeaways:

• With a customer focus (user who makes decisions about the assets) when we facilitate decision-making we are improving the reliability and availability of physical assets.
• A power system is more reliable not when we execute more maintenance actions but when we take better decisions.
• The challenge to change the maintenance process with artificial intelligence.