Speaker: Honghu Huang
Master of Microelectronics from Fudan University, with over a decade of experience in data analysis and product management roles at PDF Solutions, Huabao Fund, and Huawei HiSilicon. Currently serving as Product Director at Semitronix.
Subject: Future Trends in Semiconductor Yield Management System
Abstract:
The evolution of Yield Management System (YMS) in the semiconductor industry is expected to be driven by advancements in data analytics, automation, and integration with emerging technologies. Firstly, yield prediction and optimization will be powered by AI/ML. Deep learning models will enhance defect pattern recognition, root cause analysis (RCA), and predictive yield forecasting. Reinforcement learning may enable dynamic process adjustments in real time to minimize yield loss. Furthermore, AI is going to deep optimize resource usage (energy/materials/equipment locations) while maintaining yield targets. Secondly, big data and edge computing will be well integrated. YMS will leverage distributed computing frameworks to handle massive datasets from fab sensors, metrology, and test equipment. Edge analytics will reduce latency for critical yield-related decisions. Fusion of analytical systems among fabs, fabless and OSAT would take place. As a result, blockchain-based traceability for secure yield data can be shared across supply chains and federated learning can be used to train YMS models without exposing sensitive fab data. Thirdly, advanced process control (APC) and closed-loop systems will be well developed. Tight integration with APC tools could enable adaptive process corrections using real-time YMS feedback. Meanwhile, digital twin simulations will optimize yield strategies before physical production. Finally, cloud-native and modular architectures are becoming a trend. Microservices-based YMS is better for scalability and interoperability with Industry 4.0 ecosystems (e.g., SECS/GEM, IoT platforms), while SaaS models have lower adoption barriers for smaller fabs. In summary, future YMS software will evolve into an intelligent, autonomous system that not only reacts to yield issues but proactively prevents them through AI-driven insights and seamless integration with smart manufacturing infrastructures.