Title :
Using neural networks and 3D polynomial interpolation for the study of probe yield vs. E-test correlation. Application to sub-micronics mixed-signal technology
Author :
Montull, J. Ignacio Alonso ; Ortega, Carlos ; Sobrino, Eliseo
Author_Institution :
Microelectron. Group, Lucent Technol., Madrid, Spain
Abstract :
In the present paper we propose the use of neural networks for statistical modelling of data, as well as the use of 3D surface in order to visualise results in a very intuitive way. The scope of the paper is to present a method for extracting qualitative information from the confrontation of yield and E-test data in order to easily identify best process conditions and potential process marginality issues. The neural network approach is a new way to face determining the huge amount of raw data that yield analysis involves in the microelectronics industry
Keywords :
correlation methods; integrated circuit modelling; integrated circuit yield; interpolation; mixed analogue-digital integrated circuits; neural nets; production engineering computing; statistical analysis; 3D polynomial interpolation; 3D surface; E-test correlation; best process conditions; microelectronics industry; neural networks; probe yield; process marginality issues; qualitative information; statistical modelling; sub-micronics mixed-signal technology; yield analysis; Data visualization; Genetic expression; Interpolation; Microelectronics; Multilayer perceptrons; Network topology; Neural networks; Polynomials; Probes; Technological innovation;
Conference_Titel :
Advanced Semiconductor Manufacturing Conference and Workshop, 1999 IEEE/SEMI
Conference_Location :
Boston, MA
Print_ISBN :
0-7803-5217-3
DOI :
10.1109/ASMC.1999.798222
