By Topic

A new accurate yield prediction method for system-LSI embedded memories

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Y. Shimada ; Renesas Technol. Corp., Hyogo, Japan ; K. Sakurai

The authors propose a new accurate yield prediction method for system-LSI embedded memories to improve the productivity of chips. Their new method is based on the failure-related yield prediction method in which failure bits in memory are tested to see whether they are repairable or not by using built-in redundancies. The important concept of the new method is called "repairable matrix'' (RM). In RM, rmij=1 means that i row redundancy sets and j column redundancy sets are needed for repair, where rmij is an element of the matrix. Here, RM can indicate all the candidate combinations of the number of row and column redundancy sets for repair. The new yield prediction method using RM solves two problems, "asymmetric repair'' and "link set.'' These have a significant effect on accurate yield prediction but have not yet been approached by conventional analytical methods. The calculation of yield by the new method is demonstrated in two kinds of advanced memory devices that have different design rules, failure situations, and redundancy designs. The calculated results are consistent with the actual yield. On average, the difference in accuracy between the new method and conventional analytical methods is about 5%.

Published in:

IEEE Transactions on Semiconductor Manufacturing  (Volume:16 ,  Issue: 3 )