Call for Papers - Conference Tracks

Call for Papers

The conference welcomes submissions in the following thematic areas (but not limited to):

Track 1: Advanced Manufacturing Technologies

  • 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)

Track 2: Automation and Intelligent Control

  • 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

Track 3: Deep Learning in Manufacturing and 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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