Optimal designs of the side sensitive synthetic chart for the coefficient of variation based on the median run length and expected median run length

Yeong, Waie Chung; Lee, Ping Yin; Lim, Sok Li; Ng, Peh Sang; Khaw, Khai Wah

doi:10.1371/journal.pone.0255366

Cited by 8 publications

(3 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These designs were tested for coefficient of variation detection. Improvements in control chart topologies boosted dependability [13]. A novel Rayleigh-distributed system control chart was created from this study.…”

Section: Introductionmentioning

confidence: 99%

Shift Detection Comparison For Sized Biased And Area Biased Exponential Distributions Based Control Charts

Anjum,

Iqbal,

Kashif

et al. 2024

Migrat. Lett.

View full text Add to dashboard Cite

Probability distribution models are very helpful to solving many real-life problems. The development of new or extensions to an existing model is a very attractive area of research. Among many types of probability distribution models, weighted distributions are becoming more important for modeling data. Weighted distributions can help discover defects in manufacturing and outliers by weighting significant observations. Control charts are the most important tools to monitor process efficiency. In recent decades, researchers have focused on weighted distributions, especially those with size and area biased exponential distribution. This research introduces a novel control chart for a characteristic following a size-biased and area-biased exponential distribution to emphasize the relevance of weighted distributions. Charts are effectively determines size-biased and area-biased exponential distribution control chart limits also Monte Carlo simulations are used to assess different Average Run Length (ARL) values.

show abstract

Section: Introductionmentioning

confidence: 99%

Shift Detection Comparison For Sized Biased And Area Biased Exponential Distributions Based Control Charts

Anjum,

Iqbal,

Kashif

et al. 2024

Migrat. Lett.

View full text Add to dashboard Cite

show abstract

“…Yeong et al [ 12 ] evaluated the SS chart through the average run length ( ARL ) and expected ARL ( EARL ) criteria. Subsequently, Yeong et al [ 13 ] evaluated the SS chart through the median run length ( MRL ) and expected MRL ( EMRL ) criteria. Run lengths are commonly used to evaluate the performance of control charts, where run lengths measure the number of samples until the chart gives an out-of-control signal.…”

Section: Introductionmentioning

confidence: 99%

A side-sensitive synthetic chart for the multivariate coefficient of variation

et al. 2022

View full text Add to dashboard Cite

Control charts for the coefficient of variations (γ) are receiving increasing attention as it is able to monitor the stability in the ratio of the standard deviation (σ) over the mean (μ), unlike conventional charts that monitor the μ and/or σ separately. A side-sensitive synthetic (SS) chart for monitoring γ was recently developed for univariate processes. The chart outperforms the non-side-sensitive synthetic (NSS) γ chart. However, the SS chart monitoring γ for multivariate processes cannot be found. Thus, a SS chart for multivariate processes is proposed in this paper. A SS chart for multivariate processes is important as multiple quality characteristic that are correlated with each other are frequently encountered in practical scenarios. Based on numerical examples, the side-sensitivity feature that is included in the multivariate synthetic γ chart significantly improves the sensitivity of the chart based on the run length performance, particularly in detecting small shifts (τ), and for small sample size (n), as well as a large number of variables (p) and in-control γ (γ0). The multivariate SS chart also significantly outperforms the Shewhart γ chart, and marginally outperforms the Multivariate Exponentially Weighted Moving Average (MEWMA) γ chart when shift sizes are moderate and large. To show its implementation, the proposed multivariate SS chart is adopted to monitor investment risks.

show abstract

“…The distribution of CV is investigated in this study. Yeong et al (2021) recently adopted the side-sensitive synthetic scheme to the CV chart. The proposed chart is more sensitive than the variable sample size CV chart detecting small and moderate CV shifts.…”

Section: Introductionmentioning

confidence: 99%

Alternative Design of One-Sided Shewhart Control Charts for the Multivariate Coefficient of Variation

Chew¹

2022

JST

View full text Add to dashboard Cite

The control charting technique is an approach to quality control and was implemented in various industries. There are many control charts, where the coefficient of variation control chart was one of the common charts and greatly used in Statistical Process Control. Since most processes are multivariate, the multivariate coefficient of variation charts has received great attention in the past few years. However, the existing multivariate coefficient of variation control charts was evaluated in terms of the average run length criterion, which may misinterpret the actual performance of the charts. This paper designs an alternative for the Shewhart multivariate coefficient of variation chart by considering the median run length and expected median run-length criteria to circumvent this problem. The research on the multivariate coefficient of variation chart is very limited in the existing literature by considering the median run length criterion. This proposed chart in this paper can minimize this research gap. The formulas and algorithms of the proposed chart are presented. The outputs of the proposed charts are shown by examining the different upward and downward process shifts. Additionally, the sample sizes, the process shifts, and the variation of the run-length distribution are investigated for their effects on the proposed chart. The findings reveal that the run-length distribution’s variation is inversely proportional to the shift size. Furthermore, it shows that the variation decreases if the shift size increases.

show abstract

Optimal designs of the side sensitive synthetic chart for the coefficient of variation based on the median run length and expected median run length

Cited by 8 publications

References 36 publications

Shift Detection Comparison For Sized Biased And Area Biased Exponential Distributions Based Control Charts

Shift Detection Comparison For Sized Biased And Area Biased Exponential Distributions Based Control Charts

A side-sensitive synthetic chart for the multivariate coefficient of variation

Alternative Design of One-Sided Shewhart Control Charts for the Multivariate Coefficient of Variation

Contact Info

Product

Resources

About