Anomalyse drives up Overall Equipment Efficiency by deriving actionable insights for OEMS and asset operators, leveraging novel machine learning approaches, facilitating preventative maintenance, energy monitoring, and identifying process issues.
Use Cases
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Predictive Maintenance
Identify equipment in need of maintenance well in advance of failure so you can take action early and avoid unplanned and unnecessary downtime.
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Process Insights
Spot unusual operational conditions and events so that you can explore issues before they disrupt production.
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Energy Monitoring
Detect unusual energy usage and further reduce operation costs and materials usage by maximising asset lifespan.
What is Anomaly Detection?
Anomaly Detection is the process of analysing data to identify any abnormalities.
Using machine learning allows us to understand patterns in large sets of multi-dimensional data, providing a contextual view of what is “normal”.
Identifying when a physical asset is producing data with anomalies allows you to better monitor and maintain your assets.