A synthetic control chart for monitoring process dispersion with sample standard deviation

Huang, Huei Li; Chen, F. L.

doi:10.1016/j.cie.2004.11.001

Cited by 57 publications

(24 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the univariate case, many innovations have been proposed to improve the charts' performance, such as the CUSUM charts (see Page 1 and Reynolds and Stoumbos 2 ), the EWMA charts (see Lucas and Saccucci 3 and Costa and Rahim 4 ), the adaptive charts (see Costa 5,6 and De Magalhães et al 7 ), the double sampling charts (see Daudin 8 ) and the synthetic charts (see Wu and Spedding 9,10 , Wu et al 11 , Wu and Yeo 12 , Calzada and Scariano 13 , Davis and Woodall 14 , Scariano and Calzada 15 , Gadre and Rattihalli 16 , Chen and Huang 17 and Huang and Chen 18 ).…”

Section: Introductionmentioning

confidence: 98%

The synthetic control chart based on two sample variances for monitoring the covariance matrix

Machado

Costa

Rahim

2008

Quality & Reliability Eng

View full text Add to dashboard Cite

In this article, we propose a new statistic to control the covariance matrix of bivariate processes. This new statistic is based on the sample variances of the two quality characteristics, in short VMAX statistic. The points plotted on the chart correspond to the maximum of the values of these two variances. The reasons to consider the VMAX statistic instead of the generalized variance |S| are its faster detection of process changes and its better diagnostic feature, that is, with the VMAX statistic it is easier to identify the out-of-control variable. We study the synthetic chart based on the VMAX statistic. The proposed chart is always more efficient than the chart based on the generalized variance |S|. An example is presented to illustrate the application of the proposed chart.

show abstract

Section: Introductionmentioning

confidence: 98%

The synthetic control chart based on two sample variances for monitoring the covariance matrix

Machado

Costa

Rahim

2008

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…So, the study of a chart which can detect both upward and downward shifts in the process dispersion becomes necessary and important. Along with these ideas, we extend the one-sided synthetic charts introduced by Chen and Huang (2005) and Huang and Chen (2005) and propose a two-sided synthetic S 2 chart to monitor the process dispersion.…”

Section: Introductionmentioning

confidence: 98%

“…Chen and Huang (2005) and Huang and Chen (2005) developed the synthetic charts for monitoring the process dispersion with the sample standard deviations and sample ranges, respectively. Khilare and Shirke (2012) proposed the nonparametric synthetic chart which is a combination of the sign sub-chart and the CRL sub-chart for detecting the increases in the process variation.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of a synthetic chart for monitoring process dispersion with unknown in-control variance

Guo

Wang

Cheng

2015

Computers & Industrial Engineering

View full text Add to dashboard Cite

“…Davis and Woodall (2002) presented a Markov chain model of the synthetic X chart proposed by Wu and Spedding (2000a) and used it to evaluate the zero-state and steadystage average run length (ARL) performance. Wu et al (2001b), Huang and Chen (2005), and Chen and Huang (2005) studied the properties of the synthetic np, S, and R charts, respectively. Costa and Rahim (2006) proposed a synthetic chart based on noncentral Chisquare statistics.…”

Section: Introductionmentioning

confidence: 99%

Some Comments Regarding the Synthetic Chart

Machado

Costa

2014

Communications in Statistics - Theory and Methods

View full text Add to dashboard Cite

The steady-state average run length (ARL) is a function of the in-control probabilities of being in each nonabsorbing state. Davis and Woodall (2002) tabulated values that are significantly smaller than the steady-state ARLs, because they used the out-of-control probabilities. The synthetic chart signals when a second sample point falls beyond the control limits, no matter whether one of them falls above the centerline and the other falls below it. The side-sensitive version of the synthetic chart does not signal when the points beyond the control limits are on opposite sides. With this rule, the chart detects mean changes more quickly.

show abstract

A synthetic control chart for monitoring process dispersion with sample standard deviation

Cited by 57 publications

References 31 publications

The synthetic control chart based on two sample variances for monitoring the covariance matrix

The synthetic control chart based on two sample variances for monitoring the covariance matrix

Optimal design of a synthetic chart for monitoring process dispersion with unknown in-control variance

Some Comments Regarding the Synthetic Chart

Contact Info

Product

Resources

About