In addition to setting up monitors for predictive maintenance, TrendMiner allows users to predict the evolution of the production process based on best matching behavior patterns seen in the past. The high-performance pattern recognition capabilities allow the subject matter experts to predict performance themselves, without requiring data modeling by data scientists.
Using the predicted process evolution, appropriate action can be taken by control room personnel in case of deviations from the golden fingerprints. In this way, overall profitability can be increased by controlling on-point production and reducing costs.
The circulation flow through a plate cooler was seen to drop at the end of the dosage, causing an increase of the reactor temperature. To dose faster and reduce the cycle time, faster cooling would be needed, so this problem caused a bottleneck in production.
Using TrendMiner’s search, overlay and comparison functionalities revealed that the circulation flow always dropped around a pressure of 2.8 bars in the reactor. The cause of the problem was identified to be an internal security of the circulation pump around this pressure. The related safety security setting could be increased, freeing up extra cooling capacity and making faster dosage possible.
Following this discovery, a record production was achieved due to cycle time reduction analyses in TrendMiner. With only a few minutes cycle time reduction per batch, hundreds of thousands more kilograms of product is produced per year, directly impacting the overall profitability of the plant. On top of this, products become cleaner and more consistent in quality, which means that more batches of a product grade can be produced before cleaning is needed.