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Proceedings Paper

Evolving paradigm for fab revenue optimization
Author(s): Ramakrishna Akella; Kristin Fridgeirsdottir; Andrew Skumanich
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Paper Abstract

Historically for semiconductor processing, defects have been considered in a separate class as yield detractors and significant effort goes into detection, analysis and monitoring of defects. With the increase in complexity of nano technologies, defects now become a competent comprising only part of the overall picture of yield, or more importantly, of revenue. Given the acceleration decrease in feature sizes, there is a corresponding shift from emphasis on random defectivity to both systematical defectivity as well as parametric integrity. With the view that yield loss should be generalized to revenue loss of any type, it can then be understood that the notion of process monitoring generalizes to not just defect count, but also to be broader set of characteristic including device parameters. In this regards, the tool set for monitoring the process needs to be generalized to also include systematic and parametric inspection system. The model is that an inspection tool plus an associated algorithm is required for monitoring the variance in all critical elements. The fab must then optimize the set of tools and algorithms. Including integrated metrology tools in this optimization generalizes the revenue model further, but adds significant revenue enhancement opportunities. The issue and tradeoffs imply that the fabs must consider the full characterization needs in order to determine the proper mix of monitoring tools and algorithms.

Paper Details

Date Published: 12 July 2002
PDF: 12 pages
Proc. SPIE 4692, Design, Process Integration, and Characterization for Microelectronics, (12 July 2002); doi: 10.1117/12.475645
Show Author Affiliations
Ramakrishna Akella, Univ. at Buffalo (United States)
Kristin Fridgeirsdottir, Stanford Univ. (United States)
Andrew Skumanich, Applied Materials (United States)


Published in SPIE Proceedings Vol. 4692:
Design, Process Integration, and Characterization for Microelectronics
Alexander Starikov; Kenneth W. Tobin; Alexander Starikov, Editor(s)

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