Improving manufacturing variability control in advanced CMOS technology by using TCAD methodology

Jihong Chen; Jeff Wu; Kaiping Liu; Hong Yang; David Scott

doi:10.1117/12.537172

29 April 2004 Improving manufacturing variability control in advanced CMOS technology by using TCAD methodology

Jihong Chen, Jeff Wu, Kaiping Liu, Hong Yang, David Scott

Proceedings Volume 5378, Data Analysis and Modeling for Process Control; (2004) https://doi.org/10.1117/12.537172
Event: Microlithography 2004, 2004, Santa Clara, California, United States

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.

Citation Download Citation

Jihong Chen, Jeff Wu, Kaiping Liu, Hong Yang, and David Scott "Improving manufacturing variability control in advanced CMOS technology by using TCAD methodology", Proc. SPIE 5378, Data Analysis and Modeling for Process Control, (29 April 2004); https://doi.org/10.1117/12.537172

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available