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2016
Process Control is the active correction of a process based on the results of process monitoring. Once the process monitoring tools have detected an assignable cause, this cause is removed to bring the process back into control. This chapter presents the process control techniques under fuzziness.
Cengiz Kahraman +2 more
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Process Control is the active correction of a process based on the results of process monitoring. Once the process monitoring tools have detected an assignable cause, this cause is removed to bring the process back into control. This chapter presents the process control techniques under fuzziness.
Cengiz Kahraman +2 more
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Design Considerations and Trade-offs for Shewhart Control Charts
2021When in-control parameters are unknown, they have to be estimated using a reference sample. The control chart performance in Phase II, which is generally measured in terms of the Average Run Length (ARL) or False Alarm Rate (FAR), will vary across practitioners due to the use of different reference samples in Phase I. This variation is especially large
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Normality test by Shewhart control chart
Journal of Information and Optimization Sciences, 1999Abstract Transformed quantile-quantile (TQQ) and transformed probability-probability (TPP) plots are developed with control limits for the detection of deviations from the normal distribution. It will be shown that TQQ and TPP plots are useful methods for normality test when they are adopted with Shewhart control technique.
Jea-Young Lee +2 more
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Standardization of Shewhart Control Charts
Journal of Quality Technology, 1989(1989). Standardization of Shewhart Control Charts. Journal of Quality Technology: Vol. 21, No. 4, pp. 287-289.
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RESIDUAL ANALYSIS WITH SHEWHART CONTROL CHARTS
Quality Engineering, 1991We show that the conditions for process stability are equivalent to the conditions for the error terms of a valid regression model (one in which the least squares estimators are unbiased and have minimum variance among all unbiased estimators). By viewi..
HOWARD S. GITLOW, ROSA OPPENHEIM
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1979
The concept of a control chart was evolved by Dr. Shewhart in America in 1924 — the initial development in Britain being mainly by Dr. Dudding and W. Jennett. Dr. Shewhart suggested that the control chart should have three main objectives.
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The concept of a control chart was evolved by Dr. Shewhart in America in 1924 — the initial development in Britain being mainly by Dr. Dudding and W. Jennett. Dr. Shewhart suggested that the control chart should have three main objectives.
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About Shewhart control charts to monitor the Weibull mean
Quality and Reliability Engineering International, 2019AbstractIn this paper, a new reparametrization expressed in terms of the process mean for Weibull distribution is studied; thus, the monitoring of the process mean can be made directly. Additionally, we call attention that the asymptotic control limits for control chart by central limit theorem (CLT) may lead to a serious erroneous decision ...
Fidel Henrique Fernandes +2 more
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Combined Shewhart–EWMA control charts with estimated parameters
Journal of Statistical Computation and Simulation, 2009Shewhart and EWMA control charts can be suitably combined to obtain a simple monitoring scheme sensitive to both large and small shifts in the process mean. So far, the performance of the combined Shewhart–EWMA (CSEWMA) has been investigated under the assumption that the process parameters are known.
CAPIZZI, GIOVANNA, MASAROTTO, GUIDO
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Optimization designs of the combined Shewhart-CUSUM control charts
Computational Statistics & Data Analysis, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang Wu +3 more
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Shewhart Control Charts for Monitoring Reliability with Weibull Lifetimes
Quality and Reliability Engineering International, 2014In this paper, we present Shewhart‐type and S2 control charts for monitoring individual or joint shifts in the scale and shape parameters of a Weibull distributed process. The advantage of this method is its ease of use and flexibility for the case where the process distribution is Weibull, although the method can be applied to any distribution.
Alireza Faraz +2 more
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