A Study on the Coupled Network of Quality Chain Risk Propagation Based on <scp>MHCM</scp> and Industry 5.0

ABSTRACT In response to the challenges of information fragmentation, ambiguous risk propagation mechanisms, and insufficient cross‐stage collaboration in equipment full‐lifecycle quality management, this study redefines the equipment quality chain in the context of Industrial Internet of Things (IIoT) technology enabling the interconnection of all equipment elements. By integrating real‐time data collection technology from the IIoT, a quality risk propagation function is established to quantify single‐factor sensitivity and multi‐node coupling effects, revealing the laws of deviation accumulation and cascading amplification in risk propagation. An innovative fusion of the Multilayer Hypergraph Coupling Model (MHCM) and IoT technology is used to construct a risk propagation coupling network model, uncovering the general principles of risk propagation in the equipment quality chain. Monte Carlo simulation is used to identify key sensitive nodes and validate the rationality of the quality risk propagation function. Based on this, quality management strategies adapted to the resilient manufacturing requirements of Industry 5.0 are proposed, forming a full‐chain control system and providing a quantifiable, traceable, and interceptable quality management paradigm for complex equipment systems, effectively enhancing equipment effectiveness and economy.