Monitoring a Drilling Process Using Residual Control Charts

Messaoud, Amor; Theis, Winfried; Hering, Franz; Weihs, Claus

doi:10.1080/08982110802355869

Cited by 8 publications

(9 citation statements)

References 7 publications

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“…A residuals-based profile monitoring provides a control scheme denoted regressionadjusted control. It was first proposed by Hawkins (1991Hawkins ( , 1993 and has since appeared often in application-oriented reports that used various monitoring techniques (for example, Asadzadeh et al 2012;Messaoud et al 2009). Reviews of regressionadjusted techniques and their relative effectiveness may be found in Wade and Woodall (1993), Gani et al (2010), and Montgomery (2012).…”

Section: Median Control Chartmentioning

confidence: 99%

Customized Fetal Growth Modeling and Monitoring—A Statistical Process Control Approach

Shore

Benson-Karhi

Malamud

et al. 2014

Quality Engineering

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A statistical process control (SPC)-based methodology is developed to detect early deviations of fetal biometry from expected normal growth. Using response modeling methodology (RMM), a fetal growth model is dynamically estimated and integrated in a regression-adjusted SPC control scheme, based on a new median control chart and a control chart for residuals variation. Hadlock's reference centiles are also integrated in the monitoring scheme. Longitudinal data from normal pregnancies and those with adverse medical outcomes have been analyzed. Results show that nonsmooth growth trajectory, expressed in exceptionally large absolute deviations from predicted median values, is a good precursor to possible prenatal adverse outcomes.

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Section: Median Control Chartmentioning

confidence: 99%

Customized Fetal Growth Modeling and Monitoring—A Statistical Process Control Approach

Shore

Benson-Karhi

Malamud

et al. 2014

Quality Engineering

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“…Note that the difficulties in interpreting multiple control charts also make this strategy unattractive. For more details about the univariate control charts used in this monitoring strategy, see12. Another solution is to use a multivariate control chart.…”

Section: Monitoring Strategies: the Proposed Control Chartsmentioning

confidence: 99%

Control charts based on models derived from differential equations

Weihs

Messaoud

Raabe

2010

Quality & Reliability Eng

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The development of technical processes over time can often be adequately modelled by means of differential equations. In order to monitor such processes, control charts may be derived from stochastic models based on such differential equations. In this work, this is demonstrated for a deep-hole drilling process used for producing holes with a high length-to-diameter ratio, good surface finish and straightness. The process is subject to dynamic disturbances classified as either chatter vibration or spiraling. For chatter, a differential equation for the drilling torque and a model known to well approximate processes with similar characteristics are used to set up monitoring procedures. For spiraling a control chart can be based on a statistical model for the spectrum of the structure-born vibrations derived from a differential equation for the deflection of the boring bar.

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“…Multiple residual Shewhart assume independence and normality of the residuals, see Messaoud et al (2004), and in practice it is difficult to interpret multiple control charts. Multivariate control charts based on data depth are "distribution-free" control charts and are easy to visualize and interpret.…”

Section: Resultsmentioning

confidence: 99%

“…The important out-of-control signals are produced at 250 ≤ depth ≤ 255 mm. Messaoud et al (2004) showed that a change occurred in the process at depth=252.19 mm and they concluded that this change may indicate the presence of chatter or that chatter will start in few seconds. Table ( 1) shows that the r-chart using SD produced 99 out of control signals.…”

Section: Applicationmentioning

confidence: 99%

“…Messaoud et al (2004) used the autoregressive part of equation (3) to monitor the variation of the amplitude of the relevant frequencies of the process using residual control charts. They showed that the variation in amplitude of the relevant frequencies of the process can be approximated by the AR(1) model when the process is stable and that the nonlinear term −a t b t R 3 t−1 is not important before chatter.…”

Section: Monitoring the Process Using Multiple Residualmentioning

confidence: 99%

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Application and Use of Multivariate Control Charts in a BTA Deep Hole Drilling Process

Messaoud

Theis

Weihs

et al.

Studies in Classification, Data Analysis, and Knowledge Organization

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Abstract. Deep hole drilling methods are used for producing holes with a high length-to-diameter ratio, good surface finish and straightness. The process is subject to dynamic disturbances usually classified as either chatter vibration or spiralling. In this paper, we will focus on the application and use of multivariate control charts to monitor the process in order to detect chatter vibrations. The results showed that chatter is detected and some alarm signals occurs at time points which can be connected to physical changes of the process.

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Monitoring a Drilling Process Using Residual Control Charts

Cited by 8 publications

References 7 publications

Customized Fetal Growth Modeling and Monitoring—A Statistical Process Control Approach

Customized Fetal Growth Modeling and Monitoring—A Statistical Process Control Approach

Control charts based on models derived from differential equations

Application and Use of Multivariate Control Charts in a BTA Deep Hole Drilling Process

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