Improve Overall Equipment Effectiveness (OEE), drive world-class productivity and enable continuous improvement with industrial AI and machine learning. Further reduce process and product variation and leverage better insights for immediate action.

Decrease unplanned downtime and hit production targets, reducing the need for overtime or resources for production capacity surges. Predictable production drives more confidence in capacity planning and an optimized financial operating model.

Detect and resolve anomalies and defects earlier in the process, ensuring world-class quality leaves the dock. Machine learning anomaly detection is a closed-loop detection process that improves first-pass yield, reducing raw material spend, scrap and non-value-add rework costs.

Improve the work balance of assets and reduce costs associated with idling, starving or blocking equipment. Financially optimize maintenance strategy, applying preventive, predictive and prescriptive maintenance where it drives the most value for the operation.