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Proceedings Paper

Neural manufacturing: a novel concept for processing modeling, monitoring, and control
Author(s): Chi Yung Fu; Loren Petrich; Benjamin Law
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Paper Abstract

Semiconductor fabrication lines have become extremely costly, and achieving a good return from such a high capital investment requires efficient utilization of these expensive facilities. It is highly desirable to shorten processing development time, increase fabrication yield, enhance flexibility, improve quality, and minimize downtime. We propose that these ends can be achieved by applying recent advances in the areas of artificial neural networks, fuzzy logic, machine learning, and genetic algorithms. We use the term neural manufacturing to describe such applications. This paper describes our use of artificial neural networks to improve the monitoring and control of semiconductor process.

Paper Details

Date Published: 19 September 1995
PDF: 9 pages
Proc. SPIE 2637, Process, Equipment, and Materials Control in Integrated Circuit Manufacturing, (19 September 1995); doi: 10.1117/12.221322
Show Author Affiliations
Chi Yung Fu, Lawrence Livermore National Lab. (United States)
Loren Petrich, Lawrence Livermore National Lab. (United States)
Benjamin Law, Lawrence Livermore National Lab. (United States)


Published in SPIE Proceedings Vol. 2637:
Process, Equipment, and Materials Control in Integrated Circuit Manufacturing
Anant G. Sabnis; Ivo J. Raaijmakers, Editor(s)

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