Abstract
Statistical process control techniques have been widely used to improve processes by reducing variations and defects. In the present paper, we propose a multivariate control chart technique based on a clustering algorithm that can effectively handle a situation in which the distribution of in-control observations is inhomogeneous. A simulation study was conducted to examine the characteristics of the proposed control chart and to compare them with Hotellings T 2 multivariate control charts that are widely used in real-world processes. Moreover, an experiment with real data from the thin film transistor liquid crystal display (TFT-LCD) manufacturing process demonstrated the effectiveness and accuracy of the proposed control chart.
Original language | English |
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Pages (from-to) | 5644-5657 |
Number of pages | 14 |
Journal | International Journal of Production Research |
Volume | 51 |
Issue number | 18 |
DOIs | |
Publication status | Published - 2013 Sept 1 |
Bibliographical note
Funding Information:We thank the referees for the constructive comments and suggestions, which greatly improved the quality of the paper. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT and Future Planning (2013007724) and the Ministry of Knowledge Economy in Korea under the IT R&D Infrastructure Program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2011-(B1110-1101-0002)).
Keywords
- Hotellings T
- TFT-LCD
- bootstrap
- clustering algorithm
- multivariate control chart
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering