Highly sensitive inspection system for lithography-related faults in agile-fab - detecting algorithm for monitoring and evaluation of yield impact

The authors performed automatic detection of lithography-related faults by characteristic factors calculated from fail bit count (FBC) data. They used the autocorrelation function to define a characteristic factor for a certain lithography-related failure mode. The frequency of lithography-related faults was monitored as time series data. Also, components of the characteristic factor quantified the direction of the inclination of lithography-related patterns. They changed according to time. The origin of faults varies with patterns. Thus, it is presumed that their causes differed with each period. Fault sourcing for a failure mode was carried out by correlating machine data and the characteristic factor with /spl chi//sup 2/ test. Since the characteristic factor included only one failure factor, this test could be performed with high sensitivity. The authors classified lithography-related faults and evaluated their yield impact from their frequency and yield loss automatically.