What value can you extract from process and machine data?
Increased throughput thanks to faster root cause analysis of issues
Look at anomaly scores just prior to start of issue, or to main influencing factors of predictions of failures
Result: more efficient investigation and troubleshooting, reduction of mean time to repair
Result: more efficient investigation and troubleshooting, reduction of mean time to repair
Increased throughput and better quality thanks to incident prevention
Real-time detection of (starting) anomalies and prediction of re-occurring issues
Prediction & avoidance of unplanned stops
Faster discovery and remediation of deviations in process/product quality
Prediction & avoidance of unplanned stops
Faster discovery and remediation of deviations in process/product quality
Increased Product Quality at lower cost thanks to virtual sensors
Real-time estimation of product quality
Faster feedback to operators of product quality issues
(Optional) automatic process adjustments to keep product quality in spec at lowest cost
Faster feedback to operators of product quality issues
(Optional) automatic process adjustments to keep product quality in spec at lowest cost
Continuous process improvement thanks to diagnostic analytics
Find the factors that have the largest influence on KPIs
Do what-if analysis to predict impact of potential process improvement alternatives
Do what-if analysis to predict impact of potential process improvement alternatives
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Machines, devices and industrial equipment generate more and more data that is easier to collect using the IoT. This data is full of hard to extract valuable information about the asset's health.
YANOMALY uses artificial intelligence to automatically learn normal machine operations and detect anomalies in sensor data and log files. Add sensor validation and AI-Powered Anomaly Detection and predictive modelling to your Data Monitoring Platform with Yanomaly. |
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