Russian Federation
The paper discusses the design of a cyber-physical system for timber drying that integrates industrial controllers, IIoT technologies, and machine learning. A hierarchical architecture is proposed including the physical level, controller level, data transmission level, storage and analytics level, as well as visualization and feedback level. Data types, processing stages, and the machine learning approach are described. The system's compliance with Industry 4.0 principles is demonstrated. The expected economic effect is a 15–20% reduction in defects, a 10–15% reduction in cycle time, an 8–12% reduction in energy consumption, and a payback period of about 1.5–2 years.
timber drying, cyber-physical system, IIoT, MQTT, machine learning, PLC, adaptive control
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