Smart Factory
More efficiency and effectiveness through smart machines and industrial assets
Smart Factory Use Cases
Asset Monitoring
Asset Tracking
Process digitization
Data Sharing
Predictive Quality / Maintenance
Digital Twin
Monitor industrial assets in real time using data from sensors and PLCs, e.g.
- Temperatures
- Vibrations
- Energy consumption
Monitoring the movement of industrial assets, e.g. for
- Localization in real time
- Geofencing
- Theft detection
- Inventory
- Holistic view of production and logistics processes by integrating all relevant data and information sources
- Automated triggering of processes based on real-time data
Exchange of industrial data with participants along the supply chain:
- Overarching optimization of processes
- Data Monetization
Detect and take action on anomalies in production flow and product quality based on data:
- Failure avoidance
- Scrap reduction
- Creating a digital twin of industrial assets with real-time data
- Use of machine learning and artificial intelligence for decision support
Architecture platform features
Flexible data connectivity
Digital Twin
Scalable IoT data management
Customized dashboards
Predictive Analytics / Maintenance
Smart alerts
Secure data exchange
Individual Deployment
Connectivity to a wide variety of data from industrial assets:
- Field sensors via MQTT
- PLC via OPCUA
- Classic IT system use of standards such as Sparkplug
- Mapping the digital twins of industrial assets in the IoT platform
- Convenient device management provides a quick overview of individual assets and asset groups
Professional management of IoT data streams even for very large data volumes through the use of proven Big Data open source and cloud technologies
- Precise visualization of information from the store floor to the management level
- Multi-tenant applications for different customer groups for the provision of new services
- Use of modern data analysis methods to generate new insights
- Pattern recognition and forecasting based on collected IoT and machine data
- More proactivity through rule-based alarms when threshold values are exceeded or undercut
- In the event of production disruptions, notify individual contacts depending on the severity
- Replicate data easily and quickly between diverse plants and a global data platform
- Securely share data with suppliers and customers via APIs
The right deployment for the IoT platform for every application scenario: on-premise, cloud or hybrid.
Customer examples
Automotive Supplier
Consolidation of all manufacturing and production data in a common data lake. This enables the creation of live views and comprehensive 360-degree perspectives on all manufacturing-related data. The overall goal is to support process optimization and increase overall equipment effectiveness (OEE).
Federal Agency
The combination of OPC-UA and Kafka enables secure storage and analysis of high-frequency machine data under 10ms. This helps identify potential signs of machine failure and facilitates accurate planning of maintenance activities, supporting predictive maintenance.
Industrial textiles
Retrofitting of old production systems in the textile industry to implement an IoT monitoring solution.
Equipping the systems with external sensors and reading out the PLC (Siemens S7).
An industrial gateway wasused , which was installed on the top-hat rail in the control cabinet and sends the data via MQTT.
- Briefly explained