Lightweight CNC digital process twin framework: IIoT integration with open62541 OPC UA protocol

This research introduces a novel, lightweight Digital Process Twin (DPT)-integrated IIoT framework for CNC machining, built on a modular five-layer architecture using the open-source open62541 OPC UA protocol. The layers include: (i) Physical – microcontroller with sensors; (ii) Virtual – modeling and GM code generation; (iii) Data – OPC UA-based transfer; (iv) Interaction – visualization via custom nodes; and (v) Decision – rule-based logic and analytics. Distinctive elements include custom Node-RED nodes and AI-generated synthetic data using LSTM networks simulating 500 machining trials. This data trained five ML models to predict sensor positions with high accuracies (Random-Forest: R²(0.9994), KNN: R²(0.9998). Predictions validated key digital twin functions, including error estimation, synthetic data fidelity, and system integrity. A novel “match-rule” algorithm is also introduced linking GM codes with sensor data, enhancing traceability. Validated through a case study, the framework supports predictive maintenance and offers SMEs a cost-effective path to adopt DPT-based IIoT automation across CNC tools.