Comparison of fixed versus variable samplmg interval shewhart control charts in the presence of positively autocorrelated data

1997 ◽  
Vol 26 (1) ◽  
pp. 83-106 ◽  
Author(s):  
Victor R. Prybutok ◽  
Howard R. Clayton ◽  
Martha M. Harvey
2014 ◽  
Vol 151 ◽  
pp. 121-130 ◽  
Author(s):  
Bruno Chaves Franco ◽  
Giovanni Celano ◽  
Philippe Castagliola ◽  
Antonio Fernando Branco Costa

2014 ◽  
Vol 71 (5) ◽  
Author(s):  
Abbas Umar Farouk ◽  
Ismail Mohamad

Control charts are effective tool with regard to improving process quality and productivity, Shewhart control charts are efficiently good at detecting large shifts in a given process but very slow in detecting small and moderate shifts, such problem could be tackled through design of sensitizing rules. It has been observed that autocorrelation has an advert effect on the control charts developed under the independence assumption [1]. In this article a new EWMA control chart has been introduced with autocorrelation and some run rule schemes were introduced to enhanced the performance of the EWMA control chart when autocorrelated. The three-out-of three EWMA scheme and three-out-of- four EWMA schemes were introduced and the generated data with induced autocorrelation were used to construct the EWMA chart to sensitize the shifts presence.  Simulation of autocorrelated data were carried out for the proposed schemes which detects the shifts as soon as it occurs in the given process, the performance were evaluated using the ARL (average run length) and the results were compared with the published results of Steiner (1991) and the Saccucci (1990) which were designed for large, small and moderate shift. The results indicates that the proposed schemes are more sensitive to the shifts at ARL0=500, 300 and 200 with autocorrelation of 0.2, 0.5 and 0.9 considered in the study.


Author(s):  
SANDY D. BALKIN ◽  
DENNIS K. J. LIN

Sensitizing Rules are commonly applied to Shewhart Charts to increase their effectiveness in detecting shifts in the mean that may otherwise go unnoticed by the usual "out-of-control" signals. The purpose of this paper is to demonstrate how well these rules actually perform when the data exhibit autocorrelation compared to non-correlated data. Since most control chart data are collected as time series, it is of interest to examine the performance of Shewhart's [Formula: see text] Chart using data generated from typical time series models. In this paper, measurements arising from autoregressive (AR), moving average (MA) and autoregressive moving average (ARMA) processes are examined using Shewhart Control Charts in conjunction with several sensitizing rules. The results indicate that the rules work well when there are strong autocorrelative relationships, but are not as effective in recognizing small to moderate levels of correlation. We conclude with the recommendation to practitioners that they use a more definitive measure of autocorrelation such as the Sample Autocorrelation Function correlogram to detect dependency.


2014 ◽  
Vol 31 (8) ◽  
pp. 1565-1574 ◽  
Author(s):  
Alireza Faraz ◽  
Erwin M. Saniga ◽  
Cedric Heuchenne

2021 ◽  
Vol 69 ◽  
pp. 273-289
Author(s):  
Kim Duc Tran ◽  
Qurat-Ul-Ain Khaliq ◽  
Adel Ahmadi Nadi ◽  
Thi Hien Nguyen ◽  
Kim Phuc Tran

2014 ◽  
Vol 34 (4) ◽  
pp. 770-779 ◽  
Author(s):  
Fábio Orssatto ◽  
Marcio A. Vilas Boas ◽  
Ricardo Nagamine ◽  
Miguel A. Uribe-Opazo

The current study used statistical methods of quality control to evaluate the performance of a sewage treatment station. The concerned station is located in Cascavel city, Paraná State. The evaluated parameters were hydrogenionic potential, settleable solids, total suspended solids, chemical oxygen demand and biochemical oxygen demand in five days. Statistical analysis was performed through Shewhart control charts and process capability ratio. According to Shewhart charts, only the BOD(5.20) variable was under statistical control. Through capability ratios, we observed that except for pH the sewage treatment station is not capable to produce effluents under characteristics that fulfill specifications or standard launching required by environmental legislation.


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