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| Title | A Phase II Depth-Based Variable Dimension EWMA Control Chart for Monitoring Process Mean |
| Creator | 楊素芬 Yang, Su-Fen Lin, Yi-Chi Yeh, Arthur B. |
| Contributor | 統計系 |
| Key Words | data depth;exponentially weighted moving average;Phase II monitoring;variable dimension |
| Date | 2021-10 |
| Date Issued | 2022-04-12 |
| Summary | Statistical process control consists of tools and techniques that are useful for improving a process or ensuring that a process is in a stable and satisfactory state. In many modern industrial applications, it is critically important to simultaneously monitor two or more correlated process quality variables, thus necessitating the development of multivariate statistical process control (MSPC) as an important area of research for the new century. Nevertheless, the existing MSPC research is mostly based on the assumption that the process data follow a multinormal distribution or a known distribution. However, it is well recognized that in many applications the underlying process distribution is unknown. In practice, among a set of correlated variables to be monitored, there is oftentimes a subset of variables that are easy and/or inexpensive to measure, whereas the remaining variables are difficult and/or expensive to measure but contain information that may help more quickly detect a shift in the process mean. We are motivated to develop a Phase II control chart to monitor variable dimension (VD) mean vector for unknown multivariate processes. The proposed chart is based on the exponentially weighted moving average (EWMA) of a depth-based statistic. The proposed chart is shown to lead to faster detection of mean shifts than the existing VDT2 and VD EWMAT2 charts studied in Aparisi et al. and Epprecht et al., respectively. |
| Relation | Quality and Reliability International, Vol.37, No.6, pp.2384-2398 |
| Type | article |
| DOI | https://doi.org/10.1002/qre.2863 |
| dc.contributor | 統計系 | |
| dc.creator (作者) | 楊素芬 | |
| dc.creator (作者) | Yang, Su-Fen | |
| dc.creator (作者) | Lin, Yi-Chi | |
| dc.creator (作者) | Yeh, Arthur B. | |
| dc.date (日期) | 2021-10 | |
| dc.date.accessioned | 2022-04-12 | - |
| dc.date.available | 2022-04-12 | - |
| dc.date.issued (上傳時間) | 2022-04-12 | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/139853 | - |
| dc.description.abstract (摘要) | Statistical process control consists of tools and techniques that are useful for improving a process or ensuring that a process is in a stable and satisfactory state. In many modern industrial applications, it is critically important to simultaneously monitor two or more correlated process quality variables, thus necessitating the development of multivariate statistical process control (MSPC) as an important area of research for the new century. Nevertheless, the existing MSPC research is mostly based on the assumption that the process data follow a multinormal distribution or a known distribution. However, it is well recognized that in many applications the underlying process distribution is unknown. In practice, among a set of correlated variables to be monitored, there is oftentimes a subset of variables that are easy and/or inexpensive to measure, whereas the remaining variables are difficult and/or expensive to measure but contain information that may help more quickly detect a shift in the process mean. We are motivated to develop a Phase II control chart to monitor variable dimension (VD) mean vector for unknown multivariate processes. The proposed chart is based on the exponentially weighted moving average (EWMA) of a depth-based statistic. The proposed chart is shown to lead to faster detection of mean shifts than the existing VDT2 and VD EWMAT2 charts studied in Aparisi et al. and Epprecht et al., respectively. | |
| dc.format.extent | 448101 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Quality and Reliability International, Vol.37, No.6, pp.2384-2398 | |
| dc.subject (關鍵詞) | data depth;exponentially weighted moving average;Phase II monitoring;variable dimension | |
| dc.title (題名) | A Phase II Depth-Based Variable Dimension EWMA Control Chart for Monitoring Process Mean | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1002/qre.2863 | |
| dc.doi.uri (DOI) | https://doi.org/10.1002/qre.2863 |