Condition Monitoring

IMPROVE provides an innovative self-learning condition monitoring solution that prevents producers from unexpected breakdowns or product degradation. The outcome is translated into different software options, ready for industrial use.

Central characteristics of our data-driven condition monitoring:

• Detecting and localising anomalies from learned normal behavior models
• Providing different types of models for the anomaly detection and localisation
• Easy implementation of additional types of models and monitoring algorithms as data acquisition for learning is flexible
• Providing information about signals, last anomalies and also a live visualisation of the model
• Allowing customers to forecast problems on the machine that could lead to production stoppages
• Available as an additional after-sales service that provides regular reports of the machine ef¬ficiency throughout the lifetime
• Carrying out short-time forecast analysis to identify wrong machine settings after a product changeover or problems related to raw material changes

IMPROVE’s condition monitoring software provides an allround solution that could lead to a great change in the service procedures of automatic machines and will significantly improve the production process.

For more information, please contact our coordinator Prof. Dr Oliver Niggemann.

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