Physics-Informed Modeling and Fusion Control in Intelligent Manufacturing

Dear Colleagues,

Given the opportunities presented by the Internet of Things (IoT) and sensor networks, as well as the challenges posed by extreme conditions in intelligent manufacturing, the essence of physics-informed modeling and fusion control lies in addressing the bottleneck issues of traditional pure physical-based models and data-driven models, i.e., the interpretability of physical laws and adaptability of complex scenarios, ultimately ensuring the high-precision control of the cutting process, efficient production, and high reliability. In particular, the physics-informed modeling and fusion control has emerged as a promising direction for the "perception-diagnosis-decision-control" closed-loop system of intelligent cutting, for example, the prediction and closed-loop control of cutting force, cutting temperature, tool wear, and the surface quality of the workpiece, which integrates the data-driven fitting capability with the constraint information of physical laws. This Special Issue will address and report on recent advances and new breakthrough regarding physics-informed modeling and fusion control in intelligent manufacturing.

Authors are encouraged to submit studies covering theoretical research, simulation testing and practical applications.

Dr. Qing Li
Dr. Yu Shao
Dr. Xiang Chen
Guest Editors

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