| dc.contributor | 統計系 | |
| dc.creator (作者) | 楊素芬 | |
| dc.creator (作者) | Yang, S.F. | |
| dc.creator (作者) | Shen, Lijuan | |
| dc.date (日期) | 2020-03 | |
| dc.date.accessioned | 22-Jan-2021 09:17:27 (UTC+8) | - |
| dc.date.available | 22-Jan-2021 09:17:27 (UTC+8) | - |
| dc.date.issued (上傳時間) | 22-Jan-2021 09:17:27 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/133662 | - |
| dc.description.abstract (摘要) | Quality and loss of products are crucial factors in competitive companies, and firms widely adopt a loss function to measure the loss caused by a deviation in the quality variable from the target value. From Taguchi`s view point, it is important to monitor any deviation from the process target value. While most existing studies assume the quality variable follows a normal distribution, the distribution can in fact be skewed or deviate from normal in practice. This paper thus proposes loss-based control charts for monitoring the quality loss location or equivalently the deviation of the quality variable from the target value under a skew-normal distribution. We consider the exponentially weighted moving average (EWMA) average loss control chart, which illustrates the best performance in detecting an out-of-control loss location for a process with a left-skewed distribution. Numerical analysis demonstrates that the proposed EWMA average loss chart always performs better than the existing median loss chart for both left-skewed and right-skewed distributions. A numerical example illustrates the application of the proposed EWMA average loss control chart. | |
| dc.format.extent | 3869370 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | IEEE ACCESS, 8, 91163 - 91169 | |
| dc.subject (關鍵詞) | Control chart ; loss function ; process control ; run length ; skew-normal distribution | |
| dc.title (題名) | Loss-based control charts for monitoring non-normal process data | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1109/ACCESS.2020.2989400 | |
| dc.doi.uri (DOI) | https://doi.org/10.1109/ACCESS.2020.2989400 | |
