Proactive Yield Management using Frequent Pattern Database

We present 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) results 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 scrap or die loss that could be prevented. This practice allows for the association of spatial signatures to yield loss, thereby creating an avenue for proactive process control and yield enhancement. The implementation of fab fingerprint technology proactively generates a pareto of high impacting process steps and tools based on a pattern score enabling the production team to concentrate more efficiently on yield limiting events.