MES solutions enable real-time monitoring of KPIs across multiple lines, sites, regions, and globally. This comprehensive view allows manufacturers to detect anomalies as they occur, facilitating timely interventions. Leveraging AI algorithms, Eugenie's platform offers forward-looking alerts by predicting defects based on current anomalies. This proactive approach enables manufacturers to take corrective actions before defects occur, preventing yield losses.

Through real-time monitoring and analysis of data, Eugenie’s digital twins can identify anomalies in the soldering process or component placement. This proactive approach enables immediate corrective actions to be taken, reducing the risk of defects and improving the overall quality of SMT assemblies. By analyzing images and data in real time, the digital twins can identify defects that might be missed by human inspectors, improving overall product quality.

When defects do occur, digital twins can assist in conducting root cause analysis by analyzing historical data and comparing it with real-time data. This helps in identifying the exact source of problems, whether they are related to machine settings, component quality, or other factors, enabling manufacturers to make targeted improvements. Eugenie's AI-powered diagnostics delve deep into past defects, identifying patterns and similarities. This helps manufacturers gain valuable insights into potential issues and how to address them effectively.