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Proceedings Paper

Sophisticated yield analysis through novel data clustering and visualization
Author(s): Michael L. Jacobson; Jian Ma; Richard P. Rodrigues; Robert L. O'Donnell
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Paper Abstract

Mask manufacturing becomes more complicated with each technology generation. The number of tools and processing steps is increasing while the feature geometries and substrate materials are becoming more difficult to process. At the same time, the market demands new product introductions at a faster rate than ever before. The only way to meet all of these challenges is through faster yield (critical dimensions, defects, registration) learning. However, the rate of technology development for manufacturing has far outpaced the development of yield learning solutions. Spreadsheet-based learning tools are severely limited in their ability to handle the complex hierarchical data, and often there is not enough data available for a meaningful statistical analysis. We have deployed a novel application that greatly enhances our ability to perform commonality studies, which are a key element of yield learning. This application is based on treemapping technology, which takes advantage of the human eye's ability to detect subtle changes. Here, data is represented graphically on a two-dimensional screen. However, additional dimensions are included on the same plot through the use of size, color, and hierarchical nesting. This has enabled us to be more sophisticated in our approaches to yield learning through visualizing multidimensional correlations. In addition to improving our ability to perform commonality studies, the tool has also been used for process stability analysis, hold and excursion analysis, and several other manufacturing and engineering applications.

Paper Details

Date Published: 6 December 2004
PDF: 10 pages
Proc. SPIE 5567, 24th Annual BACUS Symposium on Photomask Technology, (6 December 2004); doi: 10.1117/12.569346
Show Author Affiliations
Michael L. Jacobson, Intel Corp. (United States)
Jian Ma, Intel Corp. (United States)
Richard P. Rodrigues, Intel Corp. (United States)
Robert L. O'Donnell, Intel Corp. (United States)

Published in SPIE Proceedings Vol. 5567:
24th Annual BACUS Symposium on Photomask Technology
Wolfgang Staud; J. Tracy Weed, Editor(s)

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