Cloud-Based Machine Data Monitoring
Challenge
The challenge was to provide companies with a simple way to collect and visualize production data from existing machine parks to increase their productivity. The goal was to create a solution that could be integrated into existing systems without extensive hardware changes or technical expertise. The solution needed to make data accessible in real-time and provide a foundation for maintenance planning and efficiency improvements.
Danish company Trendlog.io digitalizes production processes with a platform for real-time data collection, analysis, and visualization.
Solution
Trendlog.io developed the "Plug&Log Box," a retrofit solution based on the Revolution Pi Core as the central computing unit. This box efficiently captures machine data and transfers it to the cloud. Using a specially adapted software image, customers can easily configure the hardware and seamlessly connect it to the cloud-based platform.
Data visualization is provided through a browser-based dashboard that can be configured according to customer requirements. Additionally, continuous data collection enables predictive maintenance and reduces machine downtime.
Implementation
The Plug&Log Box can be seamlessly integrated into existing production systems. At its core is the Revolution Pi Core, which processes all machine data as the computing unit. Instead of conventional expansion modules, Moxa remote I/O modules are used, connected via Ethernet in a daisy-chain topology. Communication occurs via Modbus TCP, enabling efficient data collection. A specially developed software image on the RevPi allows customers to quickly set up the hardware and connect it to the cloud without extensive technical knowledge. The RevPi processes the collected machine data and sends it to the cloud. There, a browser-based, customizable dashboard displays the data in real-time.
Technologies used:
- RevPi Core with custom software image
- Moxa remote I/O modules
- Modbus TCP
- Daisy-chain topology
- Cloud connectivity
- Browser-based dashboard
Results & Outlook
The system not only enables real-time visualization of production data but also supports predictive maintenance through continuous data collection. The analysis and categorization of errors helps prevent future downtimes and increase machine capacity.
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