Neural nets for modeling, optimization, and control in semiconductor manufacturing

Roop L. Mahajan

doi:10.1117/12.367694

1 November 1999 Neural nets for modeling, optimization, and control in semiconductor manufacturing

Roop L. Mahajan

Proceedings Volume 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II; (1999) https://doi.org/10.1117/12.367694
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

This paper provides an overview of our recent work in the development of neural network models for optimization and control of electronic manufacturing processes. The concept of physical-neural network models and model transfer are described and demonstrated to be effective in building accurate neural network models economically. Process diagnostic techniques using multiple neural networks are reviewed and shown to be accurate for fault diagnosis. Finally, recent strategies in integration of statistical and neural network tools for process control are discussed. Several examples from electronics manufacturing such as chemical vapor deposition and fine pitch stencil printing are described to illustrate application of the basic concepts discussed.

Citation Download Citation

Roop L. Mahajan "Neural nets for modeling, optimization, and control in semiconductor manufacturing", Proc. SPIE 3812, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II, (1 November 1999); https://doi.org/10.1117/12.367694

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