Real-time monitoring provides increased visibility across the factory floor. Data from sensors and machines along with ERP, MES and quality systems is consolidated and visualized into interactive dashboards. Customizable timeframes not only simplify the user experience, but enable teams to compare performance across the factory floor at both broad and granular levels.
Machine learning technologies analyze historical data to identify patterns on the factory floor that have previously led to unplanned downtime or excessive changeover times. Engineers can use this data to conduct root cause analysis faster and identify process improvements across production lines. Automatic insights can also highlight opportunities for improvement that can minimize unplanned downtime or product changeover times.
Alerts are sent in real-time to factory floor personnel when anomalies are detected on the production line. These alerts allow teams to proactively fix problems, such as a machine overheating, to prevent extended periods of downtime. Alerts are customizable; for example, parameters can be set to generate an alert only if motor speed drops five times over ten minutes, not if it drops once.
