Case Study: Clariant cuts costs and cycle times with TrendMiner industrial analytics

Clariant puts the power of advanced analytics in the hands of all operational experts

Clariant, a multinational specialty chemicals company operating in 53 countries, wanted to move from descriptive and diagnostic analytics toward predictive and prescriptive capabilities while breaking down data silos across sites. Working with TrendMiner, Clariant set out to improve process understanding, connect teams across regions, and optimize production efficiency in its global chemical operations.

TrendMiner was implemented globally to analyze time-series historian data, support dashboards and reporting, and enable integrated Python notebooks for machine learning, soft sensors, and stronger golden fingerprints. The results included a 10% reduction in batch cycle time, equivalent to one extra batch per day, and a 9% reduction in consumption by energy-intensive assets, helping Clariant cut raw material usage, lower costs, and support its 2030 energy targets.

Clariant

Nimet Sterneberg

Data Scientist