Summary
A major Class 1 Railroad had been in search of a robust data collection platform to gather machine and sensor data from its facility assets, aiming to automate maintenance work orders. The pilot project was initiated in Selkirk, NY, where a SORBA-SDC data collector was integrated with one Wheel True system, running on a Rockwell Automation SLC500 with DH+ communications, and three Ingersoll Rand air compressors with MODBUS RTU communications. SORBA-SDC served as an advanced edge processor, storing sensor data locally with timestamps. The stored data was periodically transferred to a Class 1 Railroad remote endpoint via industry-standard IoT MQTT protocols.
Products and Services
Hardware
ITG proposed and deployed a robust industrial-grade SORBA-SDC data collection platform. The device came in a NEMA 4X stainless enclosure with a sun shield, suitable for outdoor use and wall-mountable. It included:
Services
The services provided encompassed:
Software and Data Handling
SORBA-SDC was configured for secure data collection, supporting integrated PLC & IO communication drivers. The device featured a 30GB SSD drive that could potentially store months or even years of data, depending on the configured frequency and data points. SORBA-SDC offered the advantage of continuous data collection, even in cases of server endpoint communication loss, ensuring zero data loss.
A communication service within SORBA-SDC packaged the data and transferred it to the designated customer endpoint using the MQTT protocol. When SORBA-SDC was configured to transfer data through a cellular network or outside of the customer network, port 1883 needed to be opened through the customer firewall. No firewall changes were required when the device was connected within the customer network.
Conclusion
The IoT Data Collection project marked a significant step towards automating and optimizing customer’s facility maintenance processes. The SORBA-SDC platform successfully provided an integrated, secure, and efficient solution for data collection and work order automation. Its implementation enabled customer to transition towards data-driven maintenance strategies, improving both reliability and operational efficiency.
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