Process experts used TrendMiner to identify inlet and steam flow timeframes and help control steam loss in a two-part filtration process.
Learn how you can use self-service analytics software to reduce downtime by setting up anomaly detection models.
The purpose of this white paper is to demonstrate how TrendMiner can help accomplish these goals. By the end of the paper, water and wastewater experts will see how the advanced self-service data analytics platform empowers engineers and manufacturing process experts to resolve challenges without the help of a data scientist.
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Before starting a root cause analysis to set up new monitors and alerts, engineers used TrendMiner to calculate steam balance.
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.