A Cloud-Edge Adaptive Framework for Equipment Predictive Maintenance in IIoT

The Industrial Internet of Things (IIoT) amalgamates cutting-edge information technologies, including artificial intelligence, big data, and cloud computing, to establish a sophisticated platform for intelligent predictive maintenance of complex industrial equipment. While numerous predictive maintenance methodologies have been proposed, much of the existing research predominantly emphasizes predictive techniques, with limited attention devoted to developing a comprehensive predictive maintenance framework. To bridge this scholarly gap, this paper proposes a novel cloud-edge adaptive framework for equipment predictive maintenance in IIoT. Positioned across the cloud, edge, and equipment planes of the IIoT infrastructure, this framework adeptly addresses challenges such as highly generalized collaborative modeling, scenario-specific modeling, and continuous dynamic evolution of equipment predictive maintenance in the Industrial Internet. Consequently, this framework offers a methodical and holistic solution to predictive maintenance for industrial equipment.