The 4th International Symposium on Artificial Intelligence and Intelligent Manufacturing will bring together leading researchers, engineers and scientists in the domain of interest from around the world.
Manuscripts passed the peer-review process by expert reviewers from the conference organizing committee will be accepted and published in the Conference Proceedings. The published papers will then be submitted to EI Compendex, Scopus, CNKI for abstracting/indexing.
The topics of interest for submission include, but are not limited to:
Artificial Intelligence Computer Vision Machine Learning Artificial Intelligence Algorithms Intelligent Manufacturing Precision Manufacturing Technology Virtual and Network Manufacturing Industrial Robots and Automated Production Lines Industrial Design and Manufacturing Intelligent Control System Mechanical Manufacturing Automation Intelligent Sensing System Aerospace Applications Electrical Control Technology Smart Factory and Automation Technology Machine learning based production optimization Deep Learning in Fault Detection and Diagnosis Machine learning-driven product quality control Predictive maintenance and real-time analytics Autonomous Robots in Manufacturing Environments |
Data-driven manufacturing process optimization Application of AR/VR technology in assembly and training Mining and Analyzing Big Data in Manufacturing Intelligent Decision Analysis and Support System Image Recognition and Localization Technology Visual Inspection and Quality Control System AI-based supply chain prediction and optimization Intelligent Warehouse System and Automated Transportation AI-assisted design and processing of new materials Role of AI in Green Manufacturing Blockchain Implementation in Supply Chain Security Architecture Design for Industrial Control Systems Cyber Threat Detection and Protection for Manufacturing Systems Multi-robot system coordination and control Human-robot collaboration and safety research Industrial Internet of Things Architecture Design and Implementation Application of digital twin technology in manufacturing
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