naa a22 4500 510821863 CHVBK 20180411083536.0 cr unu---uuuuu 180411e20130101xx s 000 0 eng 10.1007/s12541-013-0015-0 doi (NATIONALLICENCE)springer-10.1007/s12541-013-0015-0 Wafer-to-wafer process fault detection using data stream mining techniques [Elektronische Daten] [Jong Ko, Seong Hong, Ja Choi, Chang Kim] In this paper, we develop a wafer-to-wafer fault detection system using data stream mining techniques for a semiconductor etch tool. The system consists of two data stream mining modules: a trace segmentation module and a multivariate trace comparison module. Each time a wafer exits the processing chamber, the trace segmentation module extracts the traces of monitored tool parameters from raw sensor data streams. We propose a novel trace segmentation algorithm called multisensor-based trace segmentation. The algorithm finds the individual start and end times of monitored tool parameters in a wafer-to-wafer fashion. For analyzing faulty tool operations, the multivariate trace comparison module performs a new principal component analysis (PCA) called a trace structure-based PCA. For each tool parameter, the structural similarity distance between a template and the extracted trace is measured using a dynamic time warping algorithm. Then, the measurements are used to build the PCA model. This approach is contrasted with the traditional PCA procedure in which the trace means are used as the building blocks for the PCA model. Experiments using the data collected from a worksite reactive ion etch tool showed that the performance of the proposed system is very encouraging. Korean Society for Precision Engineering and Springer-Verlag Berlin Heidelberg, 2013 Fault detection nationallicence Semiconductor process nationallicence Data stream mining nationallicence Parameter trace segmentation nationallicence Trace structure-based principal component analysis nationallicence Dynamic time warping nationallicence Ko Jong Manufacturing Quality Assurance Team, Memory Division, Samsung Electronics Co., Ltd, 445-701, Hwasung, Gyeonggi-do, South Korea aut Hong Seong Department of Information and Industrial Engineering, Yonsei University, 120-749, Seoul, South Korea aut Choi Ja Process Solutions Research Group, POSCO Technical Research Laboratories, 790-785, Pohang, Gyeongbuk, South Korea aut Kim Chang Department of Information and Industrial Engineering, Yonsei University, 120-749, Seoul, South Korea aut International Journal of Precision Engineering and Manufacturing Korean Society for Precision Engineering 14/1(2013-01-01), 103-113 2234-7593 14:1<103 2013 14 12541 https://doi.org/10.1007/s12541-013-0015-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s12541-013-0015-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ko Jong Manufacturing Quality Assurance Team, Memory Division, Samsung Electronics Co., Ltd, 445-701, Hwasung, Gyeonggi-do, South Korea aut NATIONALLICENCE 700 1- Hong Seong Department of Information and Industrial Engineering, Yonsei University, 120-749, Seoul, South Korea aut NATIONALLICENCE 700 1- Choi Ja Process Solutions Research Group, POSCO Technical Research Laboratories, 790-785, Pohang, Gyeongbuk, South Korea aut NATIONALLICENCE 700 1- Kim Chang Department of Information and Industrial Engineering, Yonsei University, 120-749, Seoul, South Korea aut NATIONALLICENCE 773 0- International Journal of Precision Engineering and Manufacturing Korean Society for Precision Engineering 14/1(2013-01-01), 103-113 2234-7593 14:1<103 2013 14 12541 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer