When a faulty valve caused unwanted flare spikes and environmental concerns, engineers used TrendMiner to find the root of the problem.

Process experts used TrendMiner’s monitoring system to compare batches and learn optimal parameters for pH, moisture, and percent of unsulfated matter.

When engineers found deviations in quality, they used TrendMiner to compare batches. With this insight, they realized the melting cycle was ending too early.

Engineers figured out they could cut their steam consumption by 165 tons per day, and learned using TrendMiner they also could produce 50 tons more ammonia.

Become-a-data-driven-factory

In this webinar, TrendMiner Data Analytics Engineer Eduardo Hernandez discusses how to easily analyze process performance and find root causes fast, monitor performance to get early warnings and predict what is likely to happen, capture events and create your own production cockpit for operational storytelling, as well as best practices to become a data-driven factory and quickly gain value.

5 Levels of PI Integration with Self-Service Analytics

Watch this webinar on demand and discover how the data captured in your PI System can be leveraged for day-to-day, data-driven decision making when it’s combined with self-service analytics capabilities.

Learn how Huntsman used TrendMiner self-service analytics in its digitalization evolution and production optimization.

Reducing your Carbon Footprint with Advanced Analytics

In this webinar, TrendMiner Customer Success Manager Daniel Münchrath discusses how pattern recognition and machine learning is used to accelerate energy transition goals and how it helps to go net-zero. He presents use cases for improving energy efficiency and explains how to perform a post-implementation review of a retrofit towards renewables using self-service analytics.

Digitalization in the Fertilizer Industry

In this webinar, Ruchika Tawani demonstrates how self-service analytics can improve the productivity, reliability and safety of fertilizer plants.