Fault clustering: modeling and observation on experimental LSI chips

Occurrence of fault clustering on large-scale integrated (LSI) MOS product was verified with optical microscopes on experimental chips that failed electrical testing. Two methods were used for determining clustering: analysis of the fault density derived from collected fault data, and separation of faults into two populations, one representing solitary faults, the other clusters. A model for the first method is presented and its effectiveness examined on a simulated fault set. The method is then applied to fault data representing two samples of MOS LSI experimental product. Population separation is finally carried out on one of the data samples, and the clustering data developed from this process are expressed by two factors. One factor can be used for refined yield estimates, the other was applied to quality measure calculations.