Abstract
Comparing frequency distributions of experimental data is a routine engineering task in the semiconductor industry. The existing statistical approaches to the problem suffer from several limitations, which can be partially overcome via the time-consuming visual examination of frequency histograms by an experienced process engineer. This paper presents a novel, fuzzy-based method for automating the cognitive process of comparing frequency histograms. We use the evolving approach of type-2 fuzzy logic to utilize the domain knowledge of human experts. The proposed method is evaluated on the actual results of an engineering experiment, where it is shown to represent the experts' perception of the visualized data more accurately than a wide range of statistical tests. We also outline the potential directions for integrating the perception-based approach with other methods of data visualization and data mining.
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