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The charting statistics of T 2 and MEWMA control charts for the phase II analysis of WhatsApp internet usage-the red values exceed the control limit.

The charting statistics of T 2 and MEWMA control charts for the phase II analysis of WhatsApp internet usage-the red values exceed the control limit.

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Figure 3. The Instagram internet usage of more frequently active...
Figure 5. The statistics of T 2 (a) and MEWMA (b) control charts from...
Figure 10. The WhatsApp internet usage of more frequently active...
The charting statistics of T 2 and MEWMA control charts for the phase...
Data-Driven Surveillance of Internet Usage Using a Polynomial Profile Monitoring Scheme
Article
Full-text available
  • Aug 2023
Control charts, which are one of the major tools in the Statistical Process Control (SPC) domain, are used to monitor a process over time and improve the final quality of a product through variation reduction and defect prevention. As a novel development of control charts, referred to as profile monitoring, the study variable is not defined as a qu...
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Context 1
... the charting statistics were computed for both approaches from the beginning of Phase II until twenty days later. The results are reported in Table 2. Both control charts could detect the unnatural situation as soon as it happened. ...

Citations

... Therefore, a possible future extension for the current research is to investigate the effect of measurement errors on the one-sided TEWMAX chart (or the one-sided REWMAX chart) with the optimized truncation point (the optimized reflecting boundary). Furthermore, using real-life data to demonstrate the implementation of control charts, for example, as done in Netshiozwi et al. [35], will be more persuasive than the simulated ones. ...
The performance of the one-sided truncated exponentially weighted moving average X-bar control chart in the presence of measurement errors
Article
  • Feb 2024
  • J STAT COMPUT SIM
When the direction of a potential mean shift can be anticipated, the one-sided exponentially weighted moving average (EWMA) X-bar control chart using the truncation method (namely, the one-sided TEWMA X-bar chart) is more efficient than those conventional one- and two-sidedEWMA X-bar schemes for process monitoring. Although attractive, there are no studies on designing the one-sided TEWMA X-bar chart by taking measurement errors into account. In this context, we investigate the effect of measurement errors on the performance of the one-sided TEWMA X-bar chart based on the linear covariate error model. Additionally, a Markov chain model is established to evaluate the run length properties of the scheme in the presence of measurement errors. Then, an optimal design procedure is developed for searching the optimal design parameters of the scheme. Based on these mentioned studies, several tables and figures are presented to evaluate the detecting performance of the scheme under different parameters of the linear covariate error model, and then a conventional one-sided EWMA X-bar chart with reflecting boundary is introduced to further study the effect of the presence and absence of measurement errors on control chart comparison studies. Simulation results show that although the detecting performance of the proposed scheme is significantly affected by measurement errors, its performance is still superior to the classic competing chart under the same comparison conditions. Finally, an illustrative example is given to show the implementation of the recommended scheme.
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