On increasing the sensitivity of moving average control chart using auxiliary variable

Amir, Muhammad Wasim; Raza, Zeeshan; Abbas, Zameer; Nazir, Hafız Zafar; Akhtar, Noureen; Riaz, Muhammad; Abid, Muhammad

doi:10.1002/qre.2790

Cited by 10 publications

(6 citation statements)

References 34 publications

(37 reference statements)

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“…Proposed control charts are compared with Refs. 47 , 33 , 51 , 44 , 9 , 25 . It is found that the proposed control chart performs better in detecting small shifts than all of these control charts.…”

Section: Discussionmentioning

confidence: 99%

Design of moving average chart and auxiliary information based chart using extended EWMA

Naveed¹,

Azam

Nawaz

et al. 2023

Sci Rep

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The control chart is the most valuable tool in the manufacturing process to track the output process in the industries. Quality specialists always want a visual framework that recognizes sustainable improvements in the monitoring processes. The efficiency of a control chart is increased by utilizing a memory-based estimator or by using any extra information relevant to the key variable. In this study, we present Extended EWMA (EEWMA) and EWMA based monitoring charts for observing the process location using moving average (MA) statistic under two different situations, i.e., when some extra information is known and unknown. We also propose an EEWMA control chart using Auxiliary Information. The output of these charts is evaluated and contrasted to the various existing charts on the basis of average run length (ARL). The comparison indicates that the proposed charts outperform rivals in identifying all types of shifts in the process location parameter. The implementation of these plans is also rendered to incorporate them in a practical situation.

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Section: Discussionmentioning

confidence: 99%

Design of moving average chart and auxiliary information based chart using extended EWMA

Naveed¹,

Azam

Nawaz

et al. 2023

Sci Rep

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“…Although adaptive schemes were initially developed to be used in memory-less control charts, studies such as Perdikis & Psarakis 7 have shown that combining both approaches (using memory-type and adaptive control charts) further improves the chart’s sensitivity and performance. Nonetheless, there are also studies such as Amir et al 8 and Abbas et al 9 that have used auxiliary information to increase the sensitivity of memory-type control charts.…”

Section: Introductionmentioning

confidence: 99%

Variable parameters memory-type control charts for simultaneous monitoring of the mean and variability of multivariate multiple linear regression profiles

Sabahno,

Eriksson

2024

Sci Rep

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Variable parameters (VP) schemes are the most effective adaptive schemes in increasing control charts' sensitivity to detect small to moderate shift sizes. In this paper, we develop four VP adaptive memory-type control charts to monitor multivariate multiple linear regression profiles. All the proposed control charts are single-chart (single-statistic) control charts, two use a Max operator and two use an SS (squared sum) operator to create the final statistic. Moreover, two of the charts monitor the regression parameters, and the other two monitor the residuals. After developing the VP control charts, we developed a computer algorithm with which the charts' time-to-signal and run-length-based performances can be measured. Then, we perform extensive numerical analysis and simulation studies to evaluate the charts’ performance and the result shows significant improvements by using the VP schemes. Finally, we use real data from the national quality register for stroke care in Sweden, Riksstroke, to illustrate how the proposed control charts can be implemented in practice.

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“…Abbas [10] introduced the double PM chart for detecting the small and medium changes in the process and showed that the proposed design perform sequentially well to its counterparts. The auxiliary information-based PM chart was created by Abbas et al ( 2019) [15], who also concluded that the suggested scheme is consistently superior to its rivals.…”

Section: Introductionmentioning

confidence: 99%

On PM t chart for monitoring changes in location parameter

Sajjad

Amir

et al. 2023

Third International Conference on Computer Vision and Data Mining (ICCVDM 2022)

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The Progressive Mean (PM) control chart is a widely recognized tool to notice the insignificant and standard variations in the process location parameter. There is one deficiency in PM chart, it generates signals which are out of control, and when the standard deviation is processed this deficiency changes the results. To overcome this problem, we proposed a method in case of not stable process stand deviation chart is used, which enables monitoring of process which is more robust in this case. The suggested chart is a participant for and charts. The numerical results concluded that the performance of the proposed chart is superior to detect small-scale and standard changes in the process parameter. To support the study an expressive application is also provided.

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On increasing the sensitivity of moving average control chart using auxiliary variable

Cited by 10 publications

References 34 publications

Design of moving average chart and auxiliary information based chart using extended EWMA

Design of moving average chart and auxiliary information based chart using extended EWMA

Variable parameters memory-type control charts for simultaneous monitoring of the mean and variability of multivariate multiple linear regression profiles

On PM t chart for monitoring changes in location parameter

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