Digital Solutions and Industrial Intelligence

A Digital Twin is a virtual replica synchronized in real time with the physical asset, using SCADA/historian data, physics models (CFD, FEA) and machine learning. It enables operational scenario simulation, predictive maintenance, process optimization and operator training without interrupting real operations.

Proctek implements IIoT with edge sensors (HART/Wireless), industrial gateways (Moxa, Advantech, Siemens MindSphere), MQTT/Kafka brokers and cloud platforms (AWS IoT, Azure IoT Hub, Google Cloud IoT). Data feeds dashboards, predictive analytics and ML models, always with IEC 62443 cybersecurity.

Proctek applies AI in predictive maintenance (models for compressors, pumps, motors), process optimization (predictive control, soft sensors), vision-based quality control, SCADA anomaly detection and critical asset failure prediction. Models are trained with historian data (PI, Ignition) and deployed at the edge or in the cloud.

Proctek applies IEC 62443 from the design stage: network zoning (Purdue model), industrial DMZ, OT-specific SIEM monitoring (Claroty, Nozomi, Dragos), change management and configuration backups, plus non-disruptive penetration testing. Compliance aligned with NIST CSF and ISO 27001.

Predictive maintenance projects on critical assets typically show ROI in 9-18 months by avoiding catastrophic failures (compressors, turbines) and reducing unplanned downtime by 20-40%. Process optimization projects pay back in 6-12 months with >2% improvement in yield or energy use. Proctek structures 90-day POCs with defined metrics before scale-up.