Case Study: Total improves uptime and efficiency with TrendMiner

Subject matter experts find faster trend analysis, diagnostics

Total Energies, a global integrated energy producer and provider, needed a faster way to turn years of operational data into actionable insights. Before TrendMiner, the company relied mainly on spreadsheets to analyze time-series and contextual manufacturing data across thousands of assets and millions of sensors, making it difficult for process experts to quickly identify root causes and improve performance.

Using TrendMiner’s self-service industrial analytics platform integrated with AVEVA PI, Total Energies was able to perform root cause analysis, build golden fingerprints, and support predictive maintenance without relying on data scientists. With TrendMiner, engineers uncovered influence factors behind process anomalies, identified an ideal main air blower startup pattern, and monitored heat exchanger fouling earlier to avoid production losses, improving uptime, efficiency, and asset performance.

Total

Fabrice Leclercq

Rotating Machinery Engineer