| 1 | Title of the Article | Time Series Approaches to Statistical Process Control |
| 2 | Author's name | Ajit Goswami: Research Scholar, Dibrugarh University,Dibrugarh, Assam, India (e-mail: agoswami09@gmail.com) |
| 3 | Author's name | |
| 4 | Subject | Statistics |
| 5 | Keyword(s) | Autocorrelation,Dependent observation, EWMA control chart,SPC |
| 6 | Abstract | In traditional Statistical Process Control (SPC)procedure, a standard assumption is that observation from the process at different time points are independent random variable. However, this independent assumption is not always true.. In fact, in the last decade, the time-series approach to Statistical Process Control has been a topic of interest of many quality scientists. In this paper, an attempt has been made to highlight some of the works in this area and a few models will be discussed to analyze the effects of autocorrelation on some standard control charts techniques. |
| 7 | Publisher | Innovative Research Publication |
| 8 | Journal Name; vol., no. | International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-1 Issue-2 |
| 9 | Publication Date | November 2013 |
| 10 | Type | Peer-reviewed Article |
| 11 | Format | |
| 12 | Uniform Resource Identifier | https://ijircst.org/view_abstract.php?title=Time-Series-Approaches-to-Statistical-Process-Control&year=2013&vol=1&primary=QVJULTEw |
| 13 | Digital Object Identifier(DOI) | |
| 14 | Language | English |
| 15 | Page No | 34-38 |