Abstract
Semiconductor industry has one of the most productive industries in Taiwan and been the role model for other countries to be competitive in this field. Due to the complex manufactory processes and limited time to meet market demands maintain high yield, silicon wafer FAB must use variable analyses and process monitering methods to improve the process efficiency, especially at the stage of new product development, engineer have to test circuit design for customers with wafer acceptance test (WAT). However, it’s time-consuming to collect data so huge amount of for determining golden die and sometimes mistakes could be made due to the different diagnose methods and experiences form engineers. This paper is to develop an approach for WAT parameter sampling analysis of golden die through data extraction and transformation at semiconductor R&D stage, Fuzzy ART, and similarity analysis. The most representative sampling die can be determined through die cluster and similarity analysis and then it can be used for engineers to find golden die corresponding with experiments on those date provided by semiconductor companies, the presented approach classifieds data into suitable clusters and the representative die for each cluster can then be selected via similarity analysis. Therefore, we can determine the die closest to the golden die and the group. This may provide engineers with information useful for that stage manufacturing to which it belongs to process analysis in the future.