The metrology-data-quality-index (DQIy) algorithm was proposed to perform metrology-data-quality evaluation of the automatic virtual metrology system developed by the authors. The DQIyalgorithm is based on the adaptive-resonance-theory 2 (ART2). ART2 divides data into different patterns according to the similarity of process data, and then calculates the corresponding DQIyvalue and its threshold, DQIyT, for evaluation and judgment. However, in practical applications, the classical ART2 technique still could not cluster process data very precisely. Since some samples with dissimilar process parameters might be sorted into the same cluster, two or more groups could be found in the corresponding metrology-data cluster. This phenomenon may cause invalid DQIydetection. To solve the problem above, the advanced ART2 scheme is proposed in this paper to enhance the accuracy of the DQIyalgorithm. A large industrial data-set showing both a shift in metrology measurements without a process shift and a process shift that was not captured by the metrology of the actual photo and color-filter production tools of a TFT-LCD factory were adopted as illustrative examples to verify the practicality of the proposed scheme. Experimental results show that the performance of the advanced ART2 is indeed better than that of the original ART2.
|Number of pages||16|
|Journal||Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A|
|Publication status||Published - 2014 Nov 1|
All Science Journal Classification (ASJC) codes