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Reinvents process monitoring and control
Panoptes VM predicts key features of a process outcome based on equipment sensor data for real-time process monitoring and control.
Reinvents process monitoring and control
Panoptes VM predicts key features of a process outcome based on equipment sensor data for real-time process monitoring and control.
Features
Panoptes VM is the industry’s first successful virtual metrology solution that predicts process outcomes reliably and robustly for real-time process monitoring and control. It tracks the temporal changes in sensor and measurement data by updating and optimizing the model continuously. Panoptes VM navigates massive data from hundreds of sensors and other metadata, and selects most relevant features for best prediction performance. By aggregating measurement data from multiple machines and tools for the same process, Panoptes VM overcomes the scarcity of the measurement data while providing precise and individualized models for the multiple machines and tools. Although all these core features are fully automatized without any manual operation, process engineers can incorporate their domain knowledge on process data and physics into main steps of predictive modeling.
Robust Prediction
provides reliable and consistent results against data drift and shift
provides reliable and consistent results against data drift and shift
Automatic Feature Selection
shows important input parameters with high impact on quality and yield
shows important input parameters with high impact on quality and yield
Flexible Customization
allows process engineers to embed domain knowledge in feature selection and modeling
allows process engineers to embed domain knowledge in feature selection and modeling
Aggregate Modeling
builds individualized models across multiple tools and machines for the same process
builds individualized models across multiple tools and machines for the same process
Automatic Model Update
enables the model to quickly relearn without any manual intervention
enables the model to quickly relearn without any manual intervention
SK hynix Deploys Gauss Labs’s AI-Based Virtual Metrology Solution to Predict Wafer Manufacturing Process Outcomes
By predicting wafer process outcomes based on sensor data, Panoptes VM reduces process variability by 21.5% on average and ultimately improves the yield as well.
Learn More
Panoptes Virtual Metrology
Reinvents process monitoring and control
Panoptes VM predicts key features of a process outcome based on equipment sensor data for real-time process monitoring and control.
Features
Panoptes VM is the industry’s first successful virtual metrology solution that predicts process outcomes reliably and robustly for real-time process monitoring and control. It tracks the temporal changes in sensor and measurement data by updating and optimizing the model continuously. Panoptes VM navigates massive data from hundreds of sensors and other metadata, and selects most relevant features for best prediction performance. By aggregating measurement data from multiple machines and tools for the same process, Panoptes VM overcomes the scarcity of the measurement data while providing precise and individualized models for the multiple machines and tools. Although all these core features are fully automatized without any manual operation, process engineers can incorporate their domain knowledge on process data and physics into main steps of predictive modeling.
Robust Prediction
provides reliable and consistent results against data drift and shift
provides reliable and consistent results against data drift and shift
Automatic Feature Selection
shows important input parameters with high impact on quality and yield
shows important input parameters with high impact on quality and yield
Flexible Customization
allows process engineers to embed domain knowledge in feature selection and modeling
allows process engineers to embed domain knowledge in feature selection and modeling
Aggregate Modeling
builds individualized models across multiple tools and machines for the same process
builds individualized models across multiple tools and machines for the same process
Automatic Model Update
enables the model to quickly relearn without any manual intervention
enables the model to quickly relearn without any manual intervention
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SK hynix Deploys Gauss Labs’s AI-Based Virtual Metrology Solution to Predict Wafer Manufacturing Process Outcomes
By predicting wafer process outcomes based on sensor data, Panoptes VM reduces process variability by 21.5% on average and ultimately improves the yield as well.
Learn More