What is Smart Monitoring?
Smart Monitoring means using data to make well-informed decisions faster. It takes over continuous asset monitoring and provides your staff with a data-driven foundation for professional decisions that only they can make. The collected data serves as an excellent foundation for long-term analysis and the prediction of potential weak points or overloads. In this way, damage can be prevented and maintenance work can be planned sensibly and carried out efficiently. Reduced costs due to failures and delays, increased safety and customer satisfaction: a win-win situation.
More transparency
Always stay one step ahead: The digital model of the factory and infrastructure allows predictions to be made on capacity utilisation, quality and possible sources of errors. The latter can thus be identified and remedied more quickly, which enables shorter downtimes.
Precise planning
Optimize the utilization and performance of your infrastructure. Shorten downtimes through better planning of jobs and maintenance.
More transparency
Always stay one step ahead: The digital model of the factory and infrastructure allows predictions to be made on capacity utilisation, quality and possible sources of errors. The latter can thus be identified and remedied more quickly, which enables shorter downtimes.
Higher maintenance effectiveness
Take the right measures at the right time: Thanks to a deep insight into the data of machines and infrastructure, you always know when and where maintenance is required - even outside of the regular service plan.
Better resilience of plants, processes and infrastructure
Keep the impairments caused by failures and maintenance to a minimum thanks to AI-supported predictive maintenance. In the event of failures, digital twins, data history and visualizations help to find and correct errors quickly.
Precise planning
Optimize the utilization and performance of your infrastructure. Shorten downtimes through better planning of jobs and maintenance.
Lower product liability risks
Protect yourself with legally compliant collection and storage of production-relevant data.
Lower maintenance and scrap costs
Keep track of the quality and reject rates produced. Thanks to Predictive Quality, you can intervene early on in the event of any problems and minimize both maintenance and scrap costs.
Higher maintenance effectiveness
Take the right measures at the right time: Thanks to a deep insight into the data of machines and infrastructure, you always know when and where maintenance is required - even outside of the regular service plan.
Lower product liability risks
Protect yourself with legally compliant collection and storage of production-relevant data.
Better resilience of plants, processes and infrastructure
Keep the impairments caused by failures and maintenance to a minimum thanks to AI-supported predictive maintenance. In the event of failures, digital twins, data history and visualizations help to find and correct errors quickly.
Lower maintenance and scrap costs
Keep track of the quality and reject rates produced. Thanks to Predictive Quality, you can intervene early on in the event of any problems and minimize both maintenance and scrap costs.
Want to see Smart Monitoring
in action?
Contact us for a free demo – no strings attached.
How does smart monitoring work?
The digital twin is a semantic model of your smart factory that integrates sensor data from various systems and is trained with AI. In the end, the twin is “smart” enough to make decisions and support employees: For example, it can point out anomalies in the monitored system (because a certain parameter is no longer within the normal range), which could be the reason for a problem that arises from it (e.g. faster wear of a part). With this information, employees can take steps to prevent the problem from occurring or to remedy it at an early stage (e.g. make adjustments to the settings of the machine or arrange for maintenance). The special thing about the Smart Monitoring Cloud: A digital twin is available out-of-the-box - you can get started right away.
1 Digital Twin
A digital twin is an effective tool for describing assets, processes, and their relationships. It learns from data collected by machines, sensors, business processes, calculations, and applications.
2 Anomaly Detection
Anomaly detection uses the digital twin to receive data streams, monitor them, identify deviations, and predict them. Furthermore, integrated AI services enable simulation, root cause analysis, intelligent tracking, and planning optimization.
Use Case: Manufacturing
Predictive Quality
Prediction of the quality produced by analyzing the real-time data from digitally networked machines and systems
1
AI-assisted formation of correlation data for quality assurance based on machine signals
2
Extending the learning model to include quality features from dedicated sensors and external systems
3
Correlation of the machine signals with quality features
4
Learning of all quality results, their meaning and solutions through user / AI interaction (human-in-the-loop model)
Predictive maintenance
Prediction of weak points and maintenance needs
1
AI-supported creation of prediction KPIs based on machine signals
2
Correlation of the machine signals with error patterns (from the MES / ERP level)
3
Extending the learning model by machine state
4
Learning of all machine states, their meaning and solutions through user / AI interactions (human-in-the-loop model)
Man and machine – an unbeatable team
What makes a team unique? That it goes further than any individual.
Because in a team, the strengths of all members come together.
Use Case: Mobility
Predictive maintenance
Monitoring of rail vibrations
1
AI-supported creation of prediction KPIs based on sensor signals from
the infrastructure
2
Correlation of the sensor signals with error patterns
3
Extension of the learning model by possible states of the rail
4
Learning of all situations, their meaning and solutions through user / AI interactions (human-in-the-loop model)
Where can Smart Monitoring help?
Manufacturing
Optimize productivity and quality through data-supported forecasts and maximum transparency
Mobility
Increase the security and lifespan of critical infrastructures by analyzing real-time data
Industrial buildings
Improve compliance and working conditions for people and machines with lower maintenance costs
