On the statistical performance of quality control charts with estimated parameters / Nesma Ali Mahmoud Saleh ; Supervised Mahmoud Alsaid Mahmoud
Material type: TextLanguage: English Publication details: Cairo : Nesma Ali Mahmoud Saleh , 2016Description: 133 P. : facsimiles ; 25cmOther title:- حول الأداء الإحصائي لخرائط التحكم في حالة المعلمات المقدرة [Added title page title]
- Issued also as CD
Item type | Current library | Home library | Call number | Copy number | Status | Date due | Barcode | |
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Thesis | قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.03.01.Ph.D.2016.Ne.O (Browse shelf(Opens below)) | Not for loan | 01010110070820000 | |||
CD - Rom | مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.03.01.Ph.D.2016.Ne.O (Browse shelf(Opens below)) | 70820.CD | Not for loan | 01020110070820000 |
Thesis (Ph.D.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics
Under estimated in-control parameters, the Phase II control chart performance is expected to vary among practitioners due to the use of different Phase I data sets. Accordingly, the typical measure of Phase II control chart performance, the average run length (ARL), becomes a random variable. In the literature, control charts with estimated parameters were assessed and the appropriate amounts of Phase I data were recommended based on the in-control performance averaged across the practitioner-to-practitioner variability. In this study, aspects of the ARL distribution, such as the standard deviation of the average run length (SDARL) and some quantiles are used to quantify the between-practitioner variability in control charts performance when the process parameters are estimated. It is shown that no realistic amount of Phase I data is sufficient to have confidence that the attained in-control ARL is close to the desired value. Moreover, it is shown that even with the use of larger amounts of historical data, there is still a problem with the excessive false alarm rates. Due to the extreme difficulty of lowering the variation in the in-control ARLs, an alternative design criterion based on the bootstrap approach is recommended for adjusting the control limits. The technique is quite effective in controlling the percentage of short in-control ARLs resulting from the estimation error. Three of the most well-known univariate control charts (Shewhart, EWMA, and CUSUM), and two multivariate charts (T2, and MEWMA) are studied
Issued also as CD
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