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.
Blog Posts
Low-code and No-code AI & Analytics Solutions Yield High-Value Use Industrial Use Cases13 September 2024 - 15:19- Building a Foundation for AI & Analytics with an Industrial Data Fabric30 August 2024 - 23:12
- TrendMiner’s 2024.R2 Release; A Complete Platform to Facilitate Event Analytics and Operationalize Industrial Data8 August 2024 - 16:38
