By Topic

A yield management strategy for semiconductor manufacturing based on information theory

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
$31 $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

4 Author(s)
Weber, C. ; Sloan Sch. of Manage., MIT, Cambridge, MA, USA ; Sankaran, V. ; Tobin, K.W., Jr. ; Scher, G.

Summary form only given. Yield managers have a large but expensive arsenal of yield improvement tools and methods at their disposal. Different tools perform different functions under different conditions and some combinations of tools and methods work better than others do. Yield managers need to know which combination of tools works the most effectively and the most cost-effectively, in order to maximize the profitability of their operations. They require metrics that allows them to assess the value of apparently unrelated options. This paper uses a model based on information theory in an attempt to create an objective method of comparing technology options for yield analysis. The knowledge extraction rate per experimentation cycle and knowledge extraction rate per unit time serve as benchmarking metrics for yield learning. Combinations of four yield analysis technologies-electrical testing (ET), automatic defect classification (ADC), spatial signature analysis (SSA) and wafer position analysis (WPA)-are examined in detail to determine an optimal yield management strategy for both the R&D and volume production environments

Published in:

Management of Engineering and Technology, 1999. Technology and Innovation Management. PICMET '99. Portland International Conference on  (Volume:1 )

Date of Conference:

1999