Challenge
Rockline was becoming frustrated with its legacy systems, it was time to
elevate their ability to monitor product quality in real time. Their system for
securely transferring & visualizing sensor data from the plant floor to the
cloud created challenges in performance issue identification, trend analysis,
and scaling their analytics. The team knew that by reaching a higher level of
visibility, they could speed up decision-making and level up their production
goals.
Solution
Our team partnered with Rockline to reimagine their data visibility from the ground up. We designed and implemented a secure, modern data pipeline using Kepware and FlowFuse to collect and route sensor data into Azure IoT Hub. From there, data flowed seamlessly into Azure Data Explorer (ADX), creating a unified, scalable platform for real-time analytics and visualization. This new architecture not only replaced the retired TSM system, but also laid the groundwork for predictive analytics and smarter operations through Databricks integration and a Unified Namespace (UNS) structure.
Results/Outcomes
- Restored real-time visibility into production data
- Secure sensor data transfer to the cloud
- Faster automated reporting
- Scalable dashboards in ADX
- Foundation for predictive analytics growth
- Streamlined integration for future IoT/AI initiatives
Project Overview
This project focused on building a secure, modern data pipeline to move
Rockline’s plant-floor sensor data into the cloud for real-time monitoring
and analysis. Kepware was configured to collect key data streams from
production systems, while FlowFuse (Node-RED) acted as the orchestration
layer, formatting messages to align with a Unified Namespace (UNS)
structure before routing them onward. Azure IoT Hub provided the secure
gateway into the cloud, enabling scalable ingestion and integration with
downstream services. With the retirement of TSM, Azure Data Explorer
(ADX) became the main tool for visualization and analytics, restoring
operational insight. In addition, Databricks was integrated into Azure,
allowing sensor data to be delivered directly for machine learning and
predictive maintenance, creating a foundation for smarter, more efficient
processes.
Capabilities
- Real-time plant-to-cloud data
- UNS data model
- Secure edge-to-cloud flow
- Scalable ADX analytics
- Flexible FlowFuse orchestration
- Databricks for advanced ML
- Dashboards & insights
- Future ready IoT/AI architecture
Software Developed
- FlowFuse architecture for routing
- FlowFuse custom functions for UNS formatting
- Databricks notebooks for Azure integration & ML
- ADX queries/dashboards for visualization
Technologies
- PLCs and plant sensors
- Edge gateway with FlowFuse/Kepware
- Azure cloud infrastructure
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