Process Monitoring:
Liquid injection/formation/grading process inputs with early warning system
Dynamic simulation visualization and analytics interface
Anomaly Detection:
Identifies abnormal cells through liquid injection/formation process analysis
Feature Analysis:
Performs feature distribution analysis and generates correlation matrices
Capacity Prediction:
Real-time capacity calculation and cell classification
Batch Analytics:
Historical data review and batch-to-batch variation analysis for production optimization
Merges electrochemical models with machine learning for accurate capacity prediction and early defect detection. Provides visualization of simulation results and production analytics, significantly improving energy efficiency and reducing capital expenditure in capacity grading processes.