The Generalized Synthetic Chart

Scariano, Stephen M.; Calzada, Maria E.

doi:10.1080/07474940802619261

Cited by 48 publications

(37 citation statements)

References 8 publications

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“…Instead, only when two signals (two nonconforming samples) occur too closely together (within inspection points of each other) is there sufficient evidence to signal an out-of-control status. Scariano and Calzada [19] developed formulae for the average run length and the standard deviation of the run length for the generalized synthetic chart, which are given in equations (1) and (2) …”

Section: The Generalized Synthetic Chartmentioning

confidence: 99%

“…Davis and Woodall [12] discussed improving the synthetic control chart, while Calzada and Scariano [3] evaluated its robustness characteristics. Scariano and Calzada [19] generalized the synthetic control chart so that it could be implemented with any control charting technique and developed average run length and variance of the run length expressions for charts having run lengths with known first moment, second moment, and probability mass function. Interest in the synthetic control chart has continued.…”

Section: Introductionmentioning

confidence: 99%

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The Synthetictand Synthetic EWMAtCharts

Calzada

Scariano

2013

Quality Technology & Quantitative Management

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______________________________________________________________________ Abstract:The and the exponentially weighted moving average (EWMA) charts were introduced in quality control literature for cases when users are not able to accurately estimate the process standard deviation. In this paper we present the synthetic versions of the and the EWMA-charts, and determine near-optimized control limits for these charts. The new charts are shown to have improved performance properties over the original and EWMA-t charts, while maintaining the desirable feature that the process standard deviation does not need to be estimated. t t t t t

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Section: The Generalized Synthetic Chartmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Synthetictand Synthetic EWMAtCharts

Calzada

Scariano

2013

Quality Technology & Quantitative Management

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“…After that, the synthetic chart appeals much attention due to its efficiency and effectiveness. Recently, a lot of research have been done in the synthetic chart for monitoring the shift in process mean (e.g., Aparisi & De Luna, 2009;Bourke, 2008;Calzada & Scariano, 2013a, 2013bCastagliola & Khoo, 2009;Khoo, Wu, & Atta, 2008;Khoo, Lee, Wu, Chen, & Castagliola, 2011;Khoo, Wong, Wu, & Castagliola, 2012;Machado & Costa, 2014;Scariano & Calzada, 2009;Wu, Ou, Castagliola, & Khoo, 2010;Yeong, Khoo, Zhang, & Castagliola, 2012;Yeong, Khoo, Lee, & Rahim, 2013).…”

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

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“…However, the EWMA and CUSUM charts are still superior to the synthetic chart in detecting small to moderate shifts. The synthetic chart has also been studied by others for monitoring attribute data (such as by combining a np chart and a CRL chart) and multivariate data (such as by combining a Hotelling's T 2 chart and a CRL chart) [43], [44], [45], [46]. The optimal statistical and economic designs of the synthetic chart have also been developed [47], [48].…”

Section: Introductionmentioning

confidence: 99%

Synthetic-Type Control Charts for Time-Between-Events Monitoring

2013

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This paper proposes three synthetic-type control charts to monitor the mean time-between-events of a homogenous Poisson process. The first proposed chart combines an Erlang (cumulative time between events, Tr) chart and a conforming run length (CRL) chart, denoted as Synth-Tr chart. The second proposed chart combines an exponential (or T) chart and a group conforming run length (GCRL) chart, denoted as GR-T chart. The third proposed chart combines an Erlang chart and a GCRL chart, denoted as GR-Tr chart. By using a Markov chain approach, the zero- and steady-state average number of observations to signal (ANOS) of the proposed charts are obtained, in order to evaluate the performance of the three charts. The optimal design of the proposed charts is shown in this paper. The proposed charts are superior to the existing T chart, Tr chart, and Synth-T chart. As compared to the EWMA-T chart, the GR-T chart performs better in detecting large shifts, in terms of the zero- and steady-state performances. The zero-state Synth-T4 and GR-Tr (r = 3 or 4) charts outperform the EWMA-T chart for all shifts, whereas the Synth-Tr (r = 2 or 3) and GR-T 2 charts perform better for moderate to large shifts. For the steady-state process, the Synth-Tr and GR-Tr charts are more efficient than the EWMA-T chart in detecting small to moderate shifts.

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The Generalized Synthetic Chart

Cited by 48 publications

References 8 publications

The Synthetictand Synthetic EWMAtCharts

The Synthetictand Synthetic EWMAtCharts

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

Synthetic-Type Control Charts for Time-Between-Events Monitoring

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