Modified Shewhart Control Chart Based on CEV for Gamma Distributed Lifetimes in the Presence of Type-I Censored Data
Syed Muhammad Muslim Raza () and
Muhammad Moeen
Additional contact information
Syed Muhammad Muslim Raza: Department of Mathematics and Statistics, Virtual University, Pakistan
Muhammad Moeen: School of Business and Economics, University of Management and Technology (UMT), Pakistan.
Journal of Quantitative Methods, 2018, vol. 2, issue 1, 114-125
Abstract:
This article explains the modified version of Shewhart control charts for monitoring the mean level of the Gamma lifetimes under the Type-I censored data. Shewhart control chart based on the conditional expected values (CEV) is developed which can efficiently monitor the Type-I censored. The results of the proposed control chart are compared with simple/traditional Shewhart control chart using different censoring rates (Pc). The main focus is the stability of the mean level for which we have considered the specified parameter(s) as well as the unspecified parameter(s) cases (where Maximum Likelihood Estimates (MLE) has been considered). It is observed that in the presence of Type-I censored observation the CEV Shewhart Control chart outperforms traditional Shewhart control chart. The proposed censoring control charts always outperform when known parameters are used rather than the MLE estimate cases. The proposed charting methodology is also illustrated by an example.
Keywords: conditional expected values (CEV); Gamma lifetimes; outperforms; Shewhart control charts; Type-I censored (search for similar items in EconPapers)
JEL-codes: C46 (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
https://ojs.umt.edu.pk/index.php/jqm/article/view/23/19 Full text (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ris:jqmumt:0011
Access Statistics for this article
Journal of Quantitative Methods is currently edited by Sajid Ali
More articles in Journal of Quantitative Methods from University of Management and Technology, Lahore, Pakistan Department of Quantitative Methods, School of Business and Economics, University of Management and Technology, Lahore, Pakistan. Contact information at EDIRC.
Bibliographic data for series maintained by Romila Qamar ().