Process experts used TrendMiner to identify inlet and steam flow timeframes and help control steam loss in a two-part filtration process.
A drop in sulfur recovery could have environmental and regulatory effects, so engineers used TrendMiner to save this solution for the future.
Engineers used TrendMiner to create condition-based monitoring of fouling in a Pygas stripper so they knew the right time to clean.
This petrochemical plant used TrendMiner to create energy balance models and determine when 17 bar steam consumption was excessive.
When a low-density polyethylene reactor suddenly shutdown after maintenance, engineers used TrendMiner to determine it was human error.
Learn how Huntsman used TrendMiner self-service analytics in its digitalization evolution and production optimization.
Six Sigma is one of the most well known methods to transform whole organizations into a data-driven and continuously improving company.
The first steps may be hard, but in this white paper, we outline how you can start digitalization process small and scale fast with various use cases based on the level of expertise so you can continuously benefit from your investment in TrendMiner.
In this webinar, LNS Research will explain why companies today are empowering plant personnel with analytics that deliver real-time insights.
In this updated introductory video, Jeroen De Wolf discusses how to empower process and asset experts with existing data to analyze, monitor and predict process performance, without depending on data scientists.