Application of machine learning techniques to semiconductor manufacturing

Keki B. Irani; Jie Cheng; Usama M. Fayyad; Zhaogang Qian

doi:10.1117/12.21147

1 January 1990 Application of machine learning techniques to semiconductor manufacturing

Keki B. Irani, Jie Cheng, Usama M. Fayyad, Zhaogang Qian

Proceedings Volume 1293, Applications of Artificial Intelligence VIII; (1990) https://doi.org/10.1117/12.21147
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

The advancement of VLSI technology has reached the stage where the automation of semiconductor manufacturing has become imminent. A natural step towards this end is to apply the available expert system technology to the task of intelligent control, monitoring and diagnosis of various processes and equipment for the IC manufacturing environment. This paper gives an overview of a machine learning program (GID3) and its use in automating the knowledge acquisition needed for the construction of an expert system for controlling the Reactive Ion Etching (RIE) process in IC manufacturing. We argue the appropriateness and necessity of machine learning to circumvent the “knowledge acquisition bottleneck”. We then motivate and describe the learning algorithm we developed. The GID3 system was applied to five different projects with several SRC industrial institutions. We describe some of the application areas where an acceptable level of success was achieved by the program. The application areas include: identification of relationships between RIE process anomalies and the corresponding parameter settings, acquiring a set of rules for correcting RIE process parameters contributing to abnormal output, and knowledge acquisition for an emitter piloting advisory expert system. The main theme of this paper is to bring attention to machine learning as a useful tool in the automation of the IC manufacturing process and as an aid to engineers in interpreting and assimilating experimental results.

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Keki B. Irani, Jie Cheng, Usama M. Fayyad, and Zhaogang Qian "Application of machine learning techniques to semiconductor manufacturing", Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); https://doi.org/10.1117/12.21147

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