The Human Hand: Curating Good Data And Creating An Effective Deep-Learning R2R Strategy For High-Volume Manufacturing

Currently, the semiconductor manufacturing industry uses artificial intelligence and machine learning to take data and autonomously learn from that data. With the additional data, AI and ML can be used to quickly discover patterns and determine correlations in various applications, most notably those applications involving metrology and inspection, whether in the front-end of the manufacturing ... » read more

Fab Fingerprint For Proactive Yield Management

The following paper presents a case study describing how to improve yield and fab productivity by implementing a frequent pattern database that utilizes artificial intelligence-based spatial pattern recognition (SPR) and wafer process history. This is important because associating spatial yield issues with process and tools is often performed as a reactive analysis, resulting in increased wafer... » read more