Predictive Analytics at Ciner with the PI System and Falkonry

Ciner Resources, a global leader in soda ash production, faced a situation common in the industrial world. Investments in instrumentation and data collection were producing large volumes of operational data, but efforts to turn this data into meaningful improvements in operational efficiency were falling short.

Attempts to use statistical analytics or approximate engineering models proved to be time consuming and limited in applicability. While machine learning techniques held promise, any approach that required an external team of data science and software experts was a non-starter. Ciner needed an approach that empowered their process engineers to use their data and their deep understanding of the plant to gain better operational insights. They found that approach with Falkonry.