Nonparametric Progressive Mean Control Chart for Monitoring Process Target |
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Authors: | Saddam Akber Abbasi Arden Miller Muhammad Riaz |
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Affiliation: | 1. Department of Statistics, The University of Auckland, , Auckland, New Zealand;2. Department of Mathematics and Statistics, King Fahd University of Petroleum and Minerals, , Dhahran, KSA, Saudi Arabia;3. Department of Statistics, Quaid‐i‐Azam University, , Islamabad, Pakistan |
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Abstract: | Nonparametric control charts are widely used when the parametric distribution of the quality characteristic of interest is questionable. In this study, we proposed a nonparametric progressive mean control chart, namely the nonparametric progressive mean chart, for efficient detection of disturbances in process location or target. The proposed chart is compared with the recently proposed nonparametric exponentially weighted moving average and nonparametric cumulative sum charts using different run length characteristics such as the average run length, standard deviation of the run length, and the percentile points of the run length distribution. The comparisons revealed that the proposed chart outperformed recent nonparametric exponentially weighted moving average and nonparametric cumulative sum charts, in terms of detecting the shifts in process target. A real life example concerning the fill heights of soft drink beverage bottles is also provided to illustrate the application of the proposed nonparametric control chart. Copyright © 2012 John Wiley & Sons, Ltd. |
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Keywords: | nonparametric control chart progressive mean process location Monte Carlo simulations run length distribution |
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