Smart Factory Use Case
This workflow implements intelligent monitoring and early warning functions for industrial production workshops. It collects sensor data from the factory in real-time and automatically converts temperature units. When the temperature reaches or exceeds 50°C, the system automatically triggers a warning event and records it in the database to ensure timely response and tracking. This process effectively monitors equipment status, prevents failures caused by abnormal temperatures, and enhances equipment reliability and production safety, making it suitable for smart manufacturing and industrial IoT scenarios.
Workflow Name
Smart Factory Use Case
Key Features and Highlights
This workflow enables intelligent monitoring and alerting within industrial production workshops. It collects factory sensor data in real-time, automatically converts temperature units, and evaluates whether temperature thresholds are exceeded to trigger alert events. Alert events are automatically created via the PagerDuty system and recorded in a database, ensuring timely response and traceability of abnormal conditions.
Core Problems Addressed
- Real-time monitoring of factory equipment temperature to detect anomalies (≥50°C);
- Automatic triggering and management of equipment fault events to prevent failures or safety hazards caused by excessive temperature;
- Unified storage of equipment operational data and anomaly event data to facilitate subsequent analysis and decision support.
Application Scenarios
- Intelligent manufacturing factory equipment monitoring;
- Industrial Internet of Things (IIoT) data acquisition and anomaly alerting;
- Production line equipment status management and maintenance warning.
Main Workflow Steps
- Receive factory sensor data (temperature, equipment runtime, timestamp, etc.) in real-time through an AMQP trigger node;
- Execute a custom function to convert temperature from Celsius to Fahrenheit, enriching the data;
- Evaluate whether the temperature reaches or exceeds the 50°C threshold;
- If exceeded, automatically invoke PagerDuty to create an incident and store the incident information in the incident_data database table;
- If not exceeded, skip the anomaly handling process;
- Store equipment sensor data (temperature, equipment name, runtime, timestamp) in the machine_data database table to ensure data integrity.
Involved Systems or Services
- AMQP Message Queue (receiving factory sensor data)
- PagerDuty (automatic incident creation and management)
- CrateDB (storage of industrial data and event data)
- n8n Custom Function Node (temperature data conversion)
Target Users and Value
- Factory automation engineers and operations teams for real-time equipment monitoring and fault alerting;
- Industrial IoT solution providers to assist clients in achieving intelligent manufacturing digital transformation;
- Production managers leveraging data-driven anomaly alerts to enhance equipment reliability and production safety.