Title :
X-IDDQ: a novel defect detection technique using IDDQ data
Author :
Sharma, Ashutosh ; Jayasumana, Anura P. ; Malaiya, Yashwant K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA
Abstract :
A statistical technique X-IDDQ for extracting defect information from IDDQ data is presented that is effective for detection of defects in ICs. The technique treats the IDDQ measurements in a holistic manner to come up with a statistic X that is highly correlated to the presence of defects. X-IDDQ facilitates binning of ICs and enhances the test process by early identification of faults. The transformation metrics, for evaluating X statistic from IDDQ measurements, obtained using one batch works extremely well for different batches, facilitating its use with manufacturing-line testing.
Keywords :
fault location; integrated circuit reliability; integrated circuit testing; statistical analysis; IDDQ data; IDDQ measurements; X-IDDQ; defect correlation; defect detection technique; fault identification; integrated circuit binning; integrated circuit defect; manufacturing-line testing; principal component analysis; statistic X; statistical technique; test optimization; Circuit faults; Circuit testing; Data mining; Delay; Fault detection; Fault diagnosis; Manufacturing; Principal component analysis; Statistical analysis; Statistics; Binning; Defect Correlation; IDDQ; Optimization; Principal Component Analysis.; Test;
Conference_Titel :
VLSI Test Symposium, 2006. Proceedings. 24th IEEE
Print_ISBN :
0-7695-2514-8
DOI :
10.1109/VTS.2006.90
