An Evaluation of a GLR Control Chart for Monitoring the Process Mean

Reynolds, Marion R.; Lou, Jianying

doi:10.1080/00224065.2010.11917825

Cited by 101 publications

(103 citation statements)

References 29 publications

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“…The GLR-S chart for monitoring a sustained shift Reynolds and Lou (2010) evaluated a GLR chart designed to detect a sustained shift in µ (called the GLR-S chart) and showed that the overall performance of the GLR-S chart is at least as good as that of other control charts for detecting a wide range of sustained shifts.…”

Section: The Glr Chartsmentioning

confidence: 99%

“…Reynolds and Lou (2010) used m 1 = 400 and m 2 = 1 for evaluating the performance. The GLR-S chart will give a signal at sampling time k if R S k,m 1 ,m 2 > h GLR−S , where the control limit h GLR−S is pre-specified based on the desired in-control performance.…”

Section: The Glr Chartsmentioning

confidence: 99%

“…When there has been a sustained shift to some unknown µ(k) = µ 1 (= µ 0 + δ σ 0 ) for k > τ * , using the likelihood formula for detecting this shift, Reynolds and Lou (2010) used the following GLR-S statistic at sampling time k…”

Section: The Glr Chartsmentioning

confidence: 99%

“…GLR charts have some advantages that the size of the parameter change does not need to be specified and these charts have been shown to be very effective in a wide variety of settings in SPC applications. Recent investigations of this chart include Hawkins et al (2003), Runger and Testik (2003), Capizzi and Masarotto (2008), Zou et al (2009), Reynolds and Lou (2010), Huang et al (2012Huang et al ( , 2013, Xu et al (2012Xu et al ( , 2013, Wang and Reynolds (2013), and Reynolds et al (2013).…”

Section: Introductionmentioning

confidence: 99%

“…The problem, to detect any special cause that produces a sustained shift in µ, has been commonly studied by many researchers. Reynolds and Lou (2010) developed a GLR chart for detecting a sustained shift in µ and evaluated the performance of this GLR chart.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

GLR Charts for Simultaneously Monitoring a Sustained Shift and a Linear Drift in the Process Mean

Choi¹,

Lee²

2014

Communications for Statistical Applications and Methods

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This paper considers the problem of monitoring the mean of a normally distributed process variable when the objective is to effectively detect both a sustained shift and a linear drift. The design and application of a generalized likelihood ratio (GLR) chart for simultaneously monitoring a sustained shift and a linear drift are evaluated. The GLR chart has the advantage that when we design this chart, we do not need to specify the size of the parameter change. The performance of the GLR chart is compared with that of other control charts, such as the standard cumulative sum (CUSUM) charts and the cumulative score (CUSCORE) charts. And we compare the proposed GLR chart with the GLR charts designed for monitoring only a sustained shift and for monitoring only a linear drift. Finally, we also compare the proposed GLR chart with the chart combinations. We show that the proposed GLR chart has better overall performance for a wide range of shift sizes and drift rates relative to other control charts, when a special cause produces a sustained shift and/or a linear drift in the process mean.

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Section: The Glr Chartsmentioning

confidence: 99%

Section: The Glr Chartsmentioning

confidence: 99%

Section: The Glr Chartsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

GLR Charts for Simultaneously Monitoring a Sustained Shift and a Linear Drift in the Process Mean

Choi¹,

Lee²

2014

Communications for Statistical Applications and Methods

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Alternatives to Shewhart Charts

Ryan

2011

Statistical Methods for Quality Improvement

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Model‐based fault diagnosis for safety‐critical chemical reactors: An experimental study

Du,

Wilhite,

Kravaris

2024

AIChE Journal

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This article presents an experimental application of fault detection, isolation, and estimation in a chemical reactor system, introducing a functional observer‐based approach without the need for linear approximation. The residual signal generators, functioning as disturbance‐decoupled functional observers, provide fault size estimates and enable fault isolation through multiple generators operating independently. The experimental study focuses on the 3‐Picoline oxidation process, deriving a discrete‐time model, and constructing specific residual generators for coolant inlet temperature and feed concentration faults. Fault diagnosis employs Fast Fourier Transform (FFT) filtering and Generalized Likelihood Ratio (GLR), facilitating on‐the‐fly detection during the experiment. The effectiveness of fault detection, disturbance decoupling, and estimation is experimentally validated.

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An Evaluation of a GLR Control Chart for Monitoring the Process Mean

Cited by 101 publications

References 29 publications

GLR Charts for Simultaneously Monitoring a Sustained Shift and a Linear Drift in the Process Mean

GLR Charts for Simultaneously Monitoring a Sustained Shift and a Linear Drift in the Process Mean

Alternatives to Shewhart Charts

Model‐based fault diagnosis for safety‐critical chemical reactors: An experimental study

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