Browsing by Author "Horng, Shih-Cheng"

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A classification-based fault detection and isolation scheme for the ion implanter
(2006-11-01)
Lin, Shin-Yeu
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Horng, Shih-Cheng
;
電控工程研究所
;
Institute of Electrical and Control Engineering
We propose a classification-based fault detection and isolation scheme for the ion implanter. The proposed scheme consists of two parts: 1) the classification part and 2) the fault detection and isolation part. In the classification part, we propose a hybrid classification tree (HCT) with learning capability to classify the recipe of a working wafer in the ion implanter, and a k-fold cross-validation error is treated as the accuracy of the classification result. In the fault detection and isolation part, we propose a warning signal generation criteria based on the classification accuracy to detect and fault isolation scheme based on the HCT to isolate the actual fault of an ion implanter. We have compared the proposed classifier with the existing classification software and tested the validity of the proposed fault detection and isolation scheme for real cases to obtain successful results.
Application of an ordinal optimization algorithm to the wafer testing process
(2006-11-01)
Lin, Shin-Yeu
;
Horng, Shih-Cheng
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this correspondence, we have formulated a stochastic optimization problem to find the optimal threshold values to reduce the overkills of dies under a tolerable retest level in wafer testing process. The problem is a hard optimization problem with a huge solution space. We propose an ordinal optimization theory-based two-level algorithm to solve for a vector of good enough threshold values and compare with those obtained by others using a set of 521 real test wafers. The test results confirm the feature of controlling the retest level in our formulation, and the pairs of overkills and retests resulted from our approach are almost Pareto optimal. In addition, our approach spends only 6.05 min in total in a Pentium IV personal computer to obtain the good enough threshold values.
Ordinal optimization approach to stochastic simulation optimization problems and applications
(2006)
Lin, Shin-Yeu
;
Horng, Shih-Cheng
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose an ordinal optimization approach to solve for a good enough solution of the stochastic simulation optimization problem with huge decision-variable space. We apply the proposed ordinal optimization algorithm to G/G/1/K polling systems to solve for a good enough number-limited service discipline to minimize the weighting average waiting time. We have compared our results with those obtained by the existing service disciplines and found that our approach outperforms the existing ones. We have also used the genetic algorithm and simulated annealing method to solve the same stochastic simulation optimization problem, and the results show that our approach is much more superior in the aspects of computational efficiency and the quality of obtained solution.