By Topic

Multi-step process yield control with large system models

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

1 Author(s)
E. A. Rietman ; Lucent Technol., Bell Lab., Murray Hill, NJ, USA

We have assembled an integrated view of the entire via manufacturing process. This integrated study includes five key plasma processes that culminate in the production of vias (contact holes) on CMOS wafers. Using a neural network, we demonstrate that the key processing steps to determine the metal-one metal-two (M1M2) resistance are the thick oxide deposition and the anisotropic via etch. Of lesser significance are the etchback planarization, an isotropic etch and plasma enhanced tetra-ethoxy silane deposition. The numerical value of M1M2 resistance can be predicted ahead of time, before completion of all five processes. This prediction can be done to an accuracy of about 1 Ohm. By using adaptive neural networks, the intelligent agents can modify their predictive behavior with respect to process changes effected by the engineering staff. Our pre-production demonstration suggests that these programs could be used in feedback and feedforward control for production yield

Published in:

American Control Conference, 1997. Proceedings of the 1997  (Volume:3 )

Date of Conference:

4-6 Jun 1997