Abstract
Control charts are considered as powerful tools in detecting any shift in a process. Usually, the Shewhart control chart is used when data follows the symmetrical property of a normal distribution. In practice, the data from the industry may follow a non-symmetrical distribution or an unknown distribution. The average run length (ARL) is a significant measure to assess the performance of the control chart. The ARL may mislead when the statistic is computed from an asymmetric distribution. To handle this issue, in this paper, an ARL-unbiased hybrid exponentially weighted moving average proportion (HEWMA-p) chart is proposed for monitoring the process variance for a non-normal distribution or an unknown distribution. The efficiency of the proposed chart is compared with the existing chart in terms of ARLs. The proposed chart is more efficient than the existing chart in terms of ARLs. A real example is given for the illustration of the proposed chart in the industry.
Highlights
The aim of quality refers to the quality of those product characteristics that will appeal to potential customers
As mentioned by [14] practitioners are often not statisticians and may have problems in implementing control charts based on non-parametric approaches
Aslam et al [52] pointed out that in a general manufacturing process, an exponentially weighted moving average EWMA control chart is more efficient in detecting small process shifts
Summary
The aim of quality refers to the quality of those product characteristics that will appeal to potential customers. As mentioned by [14] practitioners are often not statisticians and may have problems in implementing control charts based on non-parametric approaches Keeping in mind this issue, several authors, including for example, references [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41] focused on designing control charts for monitoring the process mean that were easier to apply as compared to existing charts. Aslam et al [52] pointed out that in a general manufacturing process, an exponentially weighted moving average EWMA control chart is more efficient in detecting small process shifts. The structure of the proposed chart will be presented and its efficacy will be compared with [14]
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