Introduction:
Industrial motors are the backbone of modern manufacturing and process-driven industries. They power everything from conveyor belts to pumps and compressors, and their health is critical to operational efficiency and safety. However, one of the most common—and potentially devastating—issues in industrial environments is motor overheating. If not detected in time, excessive heat can cause unplanned downtime, damage expensive equipment, and lead to significant production losses.
Traditionally, monitoring motor health required periodic manual checks or expensive, siloed control systems. In the era of Industrial IoT (IIoT) and real-time analytics, we need smarter, automated, and scalable solutions.
This blog presents a real-world solution built using SnapLogic’s integration platform and OPC UA, a machine-to-machine communication protocol widely used in industrial automation. The pipeline continuously monitors motor temperature data via OPC UA in real time, and when a critical threshold is crossed (e.g., 80°C), it:
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Automatically initiates a shutdown of the affected motor,
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Notifies the maintenance/engineering team with all relevant details, and
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Logs the event into a data warehouse for auditing and root cause analysis.
Workflow:
Snaplogic Pipeline Workflow:
🔌Subscribe to OPC UA Motor Node
The pipeline initiates a subscription to the motor telemetry node using the OPC UA Subscribe Snap, which is part of SnapLogic’s OPC UA Snap Pack. This Snap establishes a secure and persistent connection to the OPC UA server, targeting a specific motor node identified by its NodeId.
Once subscribed, the Snap enters a monitoring mode, listening continuously for DataChangeNotifications emitted by the OPC UA server. These notifications represent real-time telemetry updates from the industrial motor, such as:
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Temperature
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Vibration levels
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Speed or RPM
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Voltage or current draw
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Operational status flags
The subscription is configured with:
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Sampling Interval – Frequency of data collection from the node.
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Queue Size – Buffering capability in case of burst data or delayed processing.
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Monitoring Mode – Typically set to Reporting, which ensures updates are sent only when data changes.
This design ensures low-latency, high-efficiency event collection without polling overhead. The SnapLogic pipeline can then process these real-time telemetry events downstream for further analysis, storage, or triggering conditional logic like shutdowns or alerts.
🛠️ Process Events
Once telemetry events are received from the OPC UA Subscribe Snap, the next stage of the pipeline uses the Mapper Snap to extract and process relevant event fields. These raw data events typically include:
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timestamp– When the telemetry was recorded -
nodeId– Identifier of the subscribed node -
value– Current reading (e.g., temperature in °C, vibration in mm/s) -
statusCode– OPC UA status for data quality -
sourceTimestamp– When the server captured the value
This phase involves:
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Data Normalization: Standardizing different formats and units (e.g., converting raw float values to human-readable formats or rounding).
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Field Filtering: Extracting only the required data points (e.g., temperature or vibration) while ignoring others.
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Validation: Ensuring the event contains valid data (e.g., checking status code
= Good), and filtering out noise or invalid messages.
The processed event is now structured, consistent, and enriched, enabling downstream components (like the data warehouse and temperature check logic) to act upon it efficiently.
This modular processing allows flexibility to expand logic later (e.g., integrating predictive analytics, tagging anomalies, or multi-node processing).
🌡️ Check Temperature Threshold
After processing the event data, the pipeline immediately branches to a temperature evaluation module, typically implemented using a SnapLogic Filter Snap or a Script Snap (e.g., JavaScript or Expression Snap) to assess if the motor's temperature has exceeded a critical threshold.
✅ Logic:
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The Filter Snap evaluates a condition like:
where
$.valuerepresents the parsed temperature value from the event. -
This logic can be externalized to allow configuration (e.g., per motor type or plant zone), enabling:
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Dynamic thresholds
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Thresholds stored in a parameter table or retrieved from a REST DB Lookup Snap
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⛔ Initiate Shutdown
Once a motor overheat condition is detected (e.g., temperature > 80°C), the SnapLogic pipeline triggers an automated shutdown command to prevent equipment damage or hazardous incidents.
⚙️ Implementation:
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This step typically uses a OPC UA Write Snap
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The shutdown signal sent to a motor control system that handles emergency actions
📣 Send Slack Notification
After the motor is safely shut down, it is critical to alert the maintenance or engineering team in real-time. This step ensures quick diagnostics, reduces downtime, and keeps key stakeholders informed.
💡 Purpose:
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Notify operations and maintenance staff that an automated shutdown was triggered due to overheating.
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Include actionable details like motor ID, temperature reading, timestamp, Action Taken and shutdown status
✅ Conclusion
The Industrial Motor Overheat Detection and Automated Shutdown Alert pipeline exemplifies a proactive approach to industrial IoT monitoring using OPC UA and SnapLogic. By subscribing to real-time telemetry from motor nodes, analyzing temperature data, and triggering automated shutdowns with immediate Slack notifications, the system ensures:
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✅ Enhanced equipment safety
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✅ Reduced downtime through real-time response
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✅ Streamlined communication with maintenance teams
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✅ Full audit traceability for compliance and post-event analysis
