Autocorrelated data in quality control charts
| dc.contributor.advisor | Ensor, Katherine B. | en_US |
| dc.creator | Hood, Terri Frantom | en_US |
| dc.date.accessioned | 2009-06-04T00:42:17Z | en_US |
| dc.date.available | 2009-06-04T00:42:17Z | en_US |
| dc.date.issued | 1994 | en_US |
| dc.description.abstract | Control charts are regularly developed with the assumption that the process observations have an independent relationship. However, a common occurrence in certain industries is the collection of autocorrelated data. Two approaches are investigated that deal with this issue. The time series approach is based on modeling the data with an appropriate time series model to remove the autocorrelative structure. The EWMA approach is based on modeling the observations as a weighted average of previous data. The residuals from the two approaches are plotted on control charts and the average run lengths are compared. Both methods are applied to simulations that generate in-control data and data that have strategically located nonstandard conditions. The nonstandard conditions simulated are process change, linear drift, mean shift, and variance shift. It is proposed that the time series approach tends to perform better in these situations. | en_US |
| dc.format.extent | 124 p. | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.callno | THESIS STAT. 1994 HOOD | en_US |
| dc.identifier.citation | Hood, Terri Frantom. "Autocorrelated data in quality control charts." (1994) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/13844">https://hdl.handle.net/1911/13844</a>. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/13844 | en_US |
| dc.language.iso | eng | en_US |
| dc.rights | Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder. | en_US |
| dc.subject | Statistics | en_US |
| dc.subject | Management | en_US |
| dc.title | Autocorrelated data in quality control charts | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Statistics | en_US |
| thesis.degree.discipline | Engineering | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Arts | en_US |
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