A very efficient redundancy analysis method using fault grouping

To increase device memory yield, many manufacturers use incorporated redundancy to replace faulty cells. In this redundancy technology, the implementation of an effective redundancy analysis (RA) algorithm is essential. Various RA algorithms have been developed to repair faults in memory. However, nearly all of these RA algorithms have low analysis speeds. The more densely compacted the memory is, the more testing and repair time is needed. Even if the analysis speed is very high, the RA algorithm would be useless if it did not have a normalized repair rate of 100%. In addition, when the number of added spares is increased in the memory, then the memory space that must be searched with the RA algorithms can exceed the memory space within the automatic test equipment. A very efficient RA algorithm using simple calculations is proposed in this work so as to minimize both the repair time and memory consumption. In addition, the proposed algorithm generates an optimal solution using a tree-based algorithm in each fault group. Our experiment results show that the proposed RA algorithm is very efficient in terms of speed and repair.