High accuracy in anomaly prediction, compared to traditional time-based failure estimates.
Accelerate your time to value for analytic application delivery, breaking down data silos, and integrating operational technology (OT) and business data for greater insights.
Optimize critical processes using machine learning and advanced algorithms to predict failure and prescribe solutions to augment staff competency.
Anomaly detection using sensor-based anomaly score calculation on operational devices- Example; Frequency Band Detection, Misalignment and Lidar analysis.
Performance degradation detection based on historical failures in equipment such as compressors in the presence of potentially scarce data.
Sensor-based detection of root causes of failures using physical models such as switch failures, repair history and predictive maintenance needs.
Predict lead time from first component warning to a machine shutdown given historical failures, continuous and categorical variables and operations factors.
Maintenance or activity effectiveness estimations based on group or individual operator or technician actions.
Lead time estimation based on assembly time, transfer operations and quality data.
Accelerate your time to value for analytic application delivery.
Datasheet for App EnablementSolutions to better operate assets and schedule effective maintenance activities.
Read How to Predict Anomalies“Logan Aluminum Fast-Tracks Digital Transformation With Hitachi Vantara.”
Business Transformation Leader
“Swisscom Empowers Employees and Strengthens Customer Service With A 360-Degree View of Operations.”
Head of Information Architecture