Amid the wave of Industry 4.0, folding machines are transitioning from standalone equipment into critical nodes within intelligent production systems. Traditional two-fold machines face challenges in the Industry 4.0 environment, as their limited communication interfaces and data acquisition capabilities restrict their integration potential. Retrofitting solutions include adding IoT modules to collect operational data, integrating QR code/RFID readers for product traceability, and connecting to factory networks via standard protocols such as OPC UA. Although retrofitting increases costs, it enables traditional equipment to integrate into digital production environments.

Three-fold machines are designed with greater consideration for Industry 4.0 requirements, typically featuring robust communication interfaces and data acquisition functions. As moderately complex packaging equipment, three-fold machines play a bridging role in smart factories: they receive product information from upstream forming machines to adjust folding parameters, send completion signals to downstream cartoning machines, and report production status and quality data to MES systems. The application of digital twin technology allows three-fold machines to be optimized and debugged in virtual environments, reducing trial-and-error costs in actual production.

Four-fold machines serve as core equipment in Industry 4.0 packaging lines, boasting advanced intelligence and networking capabilities. Through industrial Ethernet, they integrate deeply with various factory systems: receiving production orders from ERP, acquiring product parameters from PLM, reporting real-time status to MES, and providing equipment health data to SCADA. The application of artificial intelligence algorithms enables four-fold machines to autonomously optimize folding strategies, predict maintenance needs, and even adjust packaging solutions based on market feedback. Cloud-based collaboration allows four-fold machines distributed across different locations to share learning outcomes, accelerating overall optimization.

Edge computing plays a significant role in the intelligentization of folding machines. By performing real-time data analysis and decision-making at the device level, reliance on central systems is reduced, and response speeds are improved. For example, vision inspection systems can assess folding quality in real time at the device level, immediately adjusting parameters or rejecting defective products. Local data processing also alleviates network burdens and safeguards the privacy and security of production data.

In the Industry 4.0 environment, folding machines are not merely production tools but also data sources and decision-making nodes. By deeply integrating into digital production networks, folding machines enable more efficient, flexible, and intelligent packaging production, driving the transformation of the entire packaging industry toward intelligent manufacturing.