UCSC-CRL-96-08: MAXIMUM LIKELIHOOD ESTIMATION FOR FAILURE ANALYSIS OF SRAM CELLS USING INDUCTIVE FAULT ANALYSIS

03/01/1996 09:00 AM
Biomolecular Engineering
This paper presents an iterative maximum likelihood (ML) estimation method for statistical analysis of yield loss. By means of Inductive Fault Analysis (IFA) and circuit simulation, the map between defects and corresponding fault behaviors can be constructed for process-monitor SRAMs. Using the data from a tester describing the number of times each fault behavior occurs, the most likely causes of low yield can be identified automatically using the approaches presented in this paper without the need for physically deprocessing the defective SRAMs. To our knowledge the application of ML method using a mixture model on yield diagnosis has not appeared before in the literature.

UCSC-CRL-96-08