Quality Prediction and Control Technology Design for Intelligent Manufacturing

Dear Colleagues,

The current manufacturing process has realized informatization, and more and more manufacturing process data is being collected and stored in actual production. However, these data are not fully analyzed and utilized to improve production efficiency and quality. Instead, it has become a burden to the manufacturing companies. Intelligence is the direction of development for manufacturing companies after meeting information technology. Making full use of manufacturing data to study smart manufacturing technologies is the theme of this Special Issue. In this Special Issue, we welcome articles that focus on new technologies of production prediction and control and new methods related to intelligent manufacturing. Topics covered include product quality prediction, equipment health prediction, quality problem tracing, equipment failure tracing, production process parameter control, production control scheduling, digital twin technology for production processes, etc. Dynamic methods of improving quality and increasing production energy efficiency are of particular interest. These topics have important research significance for enterprises to improve production quality and efficiency, save energy, and reduce costs. We invite you to contribute research work that studies prediction and control method of intelligent manufacturing.

Prof. Dr. Zhifeng Liu
Dr. Congbin Yang
Guest Editors

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