Advanced manufacturing is the use of innovative technology to improve products or processes. Advanced manufacturing systems such as industrial robots, laser cutting, metal additive manufacturing, and CNC machining have become increasingly complex and dynamic. Recent advances in artificial intelligence (AI) (e.g. Deep Learning) and information technologies (e.g. 5G, Industrial Internet of Things, Big Data, Cloud/Edge Computing, etc.) have resulted in a significant paradigm shift in manufacturing.

To guarantee the quality, efficiency, and safety of manufacturing, process monitoring and optimization of these sophisticated systems are crucial. However, due to the complexity of the manufacturing process, effective process monitoring and optimization are still challenging. Recent developments in advanced sensing technologies and the new generation of data analytics technologies provide new opportunities. The efforts in both academia and industry on sensing and data analytics for advanced manufacturing systems are towards the directions of in-situ, distributed, real-time, intelligent, and autonomous. However, there are still many ongoing challenges, e.g. the accuracy and reliability of the sensors, real-time requirement for process control, extreme working environment and sensing noise, data availability and quality, the trustworthiness of AI-based models, etc.

This Special Issue aims to consolidate research efforts on innovative sensing and data analytics for process monitoring and optimization of advanced manufacturing systems. Original research and review articles discussing the state of the art are welcome.

Potential topics include but are not limited to the following:

• Condition monitoring of key equipment in advanced manufacturing systems
• Advanced sensing solutions for extreme working conditions
• Multimodal sensor fusion and data analysis
• Real-time process monitoring for metal additive manufacturing
• Process optimization and control of advanced manufacturing processes
• Digital twin-assisted process monitoring and optimization
• Prognostics and health management (PHM) applications within advanced manufacturing
• Augmented reality (AR) and virtual reality (VR) in inspection and maintenance
• Adaptive control and optimization in manufacturing
• Hybrid computing for real-time monitoring and control of manufacturing processes
• Trustworthiness in AI-enabled process monitoring