The 2026 International Conference on Advanced Manufacturing, Automation, and Deep Learning (AMADL 2026) will be held in Guangzhou, China. As a premier academic event in the field. This conference aims to bring together global researchers, engineers, and industry professionals to exchange cutting-edge insights, share innovative research achievement, and explore emerging trends in advanced manufacturing and automation.
The conference focuses on fostering interdisciplinary collaboration between academia and industry, promoting the translation of theoretical research into practical applications, and addressing key challenges in smart manufacturing systems, robotic automation, and intelligent control technologies. By providing a platform for dialogue and knowledge dissemination, AMADL 2026 seeks to drive technological breakthroughs and sustainable development in the manufacturing sector worldwide.
We cordially invite contributions from universities, research institutions, and enterprises globally. Join us to engage in high-level discussions, network with leading experts, and contribute to shaping the future of advanced manufacturing and automation.
Optical vision-guided intelligent manufacturing equipment and closed-loop control
Optical inspection and intelligent image analysis for precision manufacturing
Optical imaging-driven digital twin modeling and applications in advanced manufacturing
Additive manufacturing and 3D printing
Smart manufacturing systems and Industry 5.0
Nanomanufacturing and microfabrication technologies
Precision machining and forming processes
Sustainable and green manufacturing
Computer-aided design (CAD) and computer-aided manufacturing (CAM)
Manufacturing process optimization and scheduling
Advanced materials and their manufacturing applications
Non-traditional manufacturing processes (e.g., laser, ultrasonic)
Industrial robotics and collaborative robots (cobots)
Industrial process automation and control systems
Intelligent sensors and IoT in automation
Machine learning and AI-driven automation
Electrical automation and power systems
Welding automation and advanced joining technologies
Control theory and applications in manufacturing
Autonomous production systems and flexible manufacturing
Human-robot interaction and ergonomics
Smart logistics and supply chain automation
Deep learning-based manufacturing process monitoring and quality control
Deep neural networks for predictive maintenance and fault diagnosis in industrial equipment
Deep reinforcement learning for adaptive production scheduling and resource optimization
Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) in robotic manipulation and motion planning
Deep learning-driven digital twin modeling and real-time simulation
Graph neural networks (GNNs) for supply chain optimization and demand forecasting
Explainable deep learning (XAI) for trustable decision-making in industrial automation
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