The solution created a model which identified failure and triggered preemptive action along with a malfunction score based on Machine Learning’s (ML) decision-tree and random forest algorithms.
Select which Site you would like to reach:
Publish date:
Capgemini’s scalable yet dynamic predictive maintenance solution reduces human intervention and cost of sudden breakdown of the robotic arms by predicting genuine failure at least 1 to 2 days prior.
The solution created a model which identified failure and triggered preemptive action along with a malfunction score based on Machine Learning’s (ML) decision-tree and random forest algorithms.
Improved operating margins through cost control and cost minimizations
Capgemini’s new platform uses the latest artificial intelligence techniques and machine...