Upstream Oil & Gas Edge Intelligence

Rugged box PCs, servers, laptops and tablets provide field computing, with FPGA and GPGPU capabilities for AI/ML acceleration and local analytics.

Ethernet, serial and industrial interfaces, I/O and data acquisition connect field instrumentation. Secure connectivity supports plant and enterprise integration.

Power supplies, DC-DC conversion, custom electronics, rugged displays, panel PCs and operator consoles support an integrated field system.

Engineering spans architecture, hardware and firmware, embedded and FPGA development, mechanical ruggedisation, software integration, testing, qualification and manufacturing.

Asset health: condition monitoring, anomaly detection and Remaining Useful Life estimation can support maintenance planning, higher availability and reduced unplanned downtime.

Remote operations: real-time operational data, equipment monitoring and event/alarm management can support faster decisions and better field visibility.

AI-enabled inspection: visual condition monitoring, video analytics and defect/anomaly detection can support earlier detection, improved safety and reduced manual inspection.

Field digitalisation: connected assets, multi-protocol data acquisition and local analytics can support better operational intelligence.

The predictive-maintenance use case covers pumps, compressors, motors/generators and wellhead equipment operating in harsh and remote environments.

Inputs include vibration, temperature, pressure, current/power, runtime/cycles and process parameters such as flow and speed.

Rugged edge processing turns these inputs into health indices, anomaly detection, fault classification, Remaining Useful Life estimates and trend analysis.

Operators can use those insights for early warnings and maintenance planning. Actual health indicators and estimates depend on application-specific models and available data.

Identify the operational challenge, equipment, workflow, existing data and business impact.

Assess sensors, PLC/RTU/DCS, instrumentation, connectivity, IT/OT interfaces and environmental constraints.

Define the computing, data acquisition, connectivity, analytics, power and operator-interface architecture; engineer and validate a prototype.

Pilot on a selected asset with real operational data, validate performance, gather user feedback and assess business value.

Agree wider deployment based on the pilot, with production, integration, training/support and continuous improvement.

Detailed key features and specifications are shared based on the program requirement. Please contact Rug-Rel for more details about configuration, interfaces, and deployment fitment.