Design of Attribute Control Chart Based on Regression Estimator

Nadia Mushtaq, Dr. Muhammad Aslam, Jaffer Hussaian

Abstract


This paper presents a statistical analysis control chart for nonconforming units in quality control.
In many situations the Shewhart control charts for nonconforming units may not be suitable or
cannot be used, as for many processes, the assumptions of binomial distribution may deviate or
may provide inadequate model. In this Study we propose a new control chart based on regression
estimator of proportion based on single auxiliary variable, namely the Pr chart and compared its
performance with P and Q chart with probability to signal as a performance measure. It has been
observed that the proposed chart is superior to the P and Q chart. This study will help quality
practitioners to choose an efficient alternative to the classical P and Q charts for monitoring
nonconforming units in industrial process.

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DOI: http://dx.doi.org/10.18187/pjsor.v13i3.1418

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Title

Design of Attribute Control Chart Based on Regression Estimator

Keywords


Description

This paper presents a statistical analysis control chart for nonconforming units in quality control. In many situations the Shewhart control charts for nonconforming units may not be suitable or cannot be used, as for many processes, the assumptions of binomial distribution may deviate or may provide inadequate model. In this Study we propose a new control chart based on regression estimator of proportion based on single auxiliary variable, namely the Pr chart and compared its performance with P and Q chart with probability to signal as a performance measure. It has been observed that the proposed chart is superior to the P and Q chart. This study will help quality practitioners to choose an efficient alternative to the classical P and Q charts for monitoring nonconforming units in industrial process.

Date

2017-09-01

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 13 No. 3, 2017



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810