Abstract
Processes characterized by high dimensional and mixture data challenge traditional statistical process control charts. In this study, we propose a multivariate control chart based on the Gower distance that can handle a mixture of continuous and categorical data. An extensive simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compared it with some existing multivariate control charts. The simulation results revealed that the proposed control chart outperformed the existing charts when the number of categorical variables increases. Furthermore, we demonstrated the applicability and effectiveness of the proposed control charts through a real case study.
| Original language | English |
|---|---|
| Pages (from-to) | 1701-1707 |
| Number of pages | 7 |
| Journal | Expert Systems With Applications |
| Volume | 41 |
| Issue number | 4 PART 2 |
| DOIs | |
| Publication status | Published - 2014 |
Bibliographical note
Funding Information:The authors thank the editor and the referees, whose comments helped improving the presentation of this paper. This research was supported by 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
- Gower distance
- Mixture data
- Multivariate control charts
- Quality control
- Statistical process control
ASJC Scopus subject areas
- General Engineering
- Computer Science Applications
- Artificial Intelligence