Intelligent Sensing, Manufacturing, Operation and Maintenance for Automatic Engineering Systems

Submission Deadline: 28 February 2024 (closed) View: 203

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Summary

Intelligent sensoring, manufacturing, and operation and maintenance technologies in the engineering and industrial systems play vital roles in the research field of Intelligent Automation & Soft Computing. Intelligent sensoring, manufacturing, and operation and maintenance technologies are able to greatly boost the progress of the intelligentization, intelligentization and digitalization of industrial devices and systems. Therefore, from the perspective of Intelligent Automation & Soft Computing, engineering systems-oriented intelligent sensoring, manufacturing, operation and maintenance, and automation are a key step of the future science and technology. With the rapid development of a new generation of artificial intelligence and quantum information technologies, the applications of the intelligent sensoring, manufacturing, operation and maintenance, and computation technologies have become increasingly extensive and in-depth. Therefore, the exploration of more emerging technologies for Intelligent Automation & Soft Computing has become a research hotspot. Specifically, deep learning, transfer learning, reinforcement learning, federated learning, graph neural network, digital twin, intelligent factory, intelligent robots, MEMS, 5G/6G technology, internet of things, block chain will be applied into the research field of Intelligent Automation & Soft Computing.

The applications of new Intelligent Automation & Soft Computing technologies into the automatic engineering systems;

The applications of new intelligent sensoring and measurement technologies into the engineering and industrial systems;

The applications of new intelligent manufacturing and micro and nano-fabrication technologies into the engineering and industrial systems;

The applications of a new generation of artificial intelligence technologies into the the engineering and industrial systems;

AI-assisted prognostics and health management (PHM);

Intelligent fault diagnosis and prognosis techniques;

Advanced machine learning methods in industrial surface defect detection;

Data analytics and information fusion for condition monitoring and predictive maintenance;

Sensor data fusion in manufacturing process and product quality monitoring;

Interoperable AI architecture and techniques of manufacturing applications;

The development of data-driven, physics-based, or hybrid methods for industrial maintenance;

Transfer learning and GNNs for Intelligent sensing, manufacturing, operation and maintenance;

Integration and cooperative operation of multi-scale monitoring system;

Reliability, effectiveness and safety of intelligent technology, and so on.

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