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Proceedings Paper

Improving manufacturing variability control in advanced CMOS technology by using TCAD methodology
Author(s): Jihong Chen; Jeff Wu; Kaiping Liu; Hong Yang; David Scott
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Paper Abstract

Rapid development of a well controlled manufacturing process is a key component of marketplace success. Accomplishing this requires a thorough understanding of the effects of process variations on parametric yield. Use of Technology Computer Assisted Design (TCAD) simulations and statistical analysis can decrease the time needed to assess the manufacturability of various transistor design options, and identify the key process parameters that cause the largest variations. This paper covers a new methodology that combines Design of Experiments (DOE) with process and device simulations to generate transistor parametric statistical models. Monte-Carlo simulations are performed to generate transistor parametric sensitivities and statistical distributions. Examples of applying this methodology to 130nm technology will be given.

Paper Details

Date Published: 29 April 2004
PDF: 6 pages
Proc. SPIE 5378, Data Analysis and Modeling for Process Control, (29 April 2004); doi: 10.1117/12.537172
Show Author Affiliations
Jihong Chen, Texas Instruments Inc. (United States)
Jeff Wu, Texas Instruments Inc. (United States)
Kaiping Liu, Texas Instruments Inc. (United States)
Hong Yang, Texas Instruments Inc. (United States)
David Scott, Texas Instruments Inc. (United States)


Published in SPIE Proceedings Vol. 5378:
Data Analysis and Modeling for Process Control
Kenneth W. Tobin, Editor(s)

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