Counterfactual causal models predict which control function change is most likely to deliver the target effect without modifying the real process.
Segmenting battery test data by charging and discharging state improves defect sorting power and cuts false positives for atypical patterns.
Early cycle measurement data is converted into a lifetime probability distribution, cutting retraining needs and reducing long-term prediction error.