Pampa Energía needed a reliable method to detect early equipment anomalies, optimize maintenance, and reduce unexpected failures and costs.

Using AVEVA PI System, we implemented Statistical Quality Control [SQC] analytics across 2,796 variables and nine power generation assets [including thermal power plants, hydroelectric plants, and wind farms], integrating critical variable modeling [18,572 analyses performed] with financial data to quantify cost avoidance. 

This centralized monitoring solution minimizes false positives, prioritizes real issues, and enhances predictive maintenance.

The result: improved reliability, measurable cost savings, and data-driven decision-making for more efficient and profitable operations.