Combined Shewhart–EWMA control charts with estimated parameters

2010 ◽  
Vol 80 (7) ◽  
pp. 793-807 ◽  
Author(s):  
Giovanna Capizzi ◽  
Guido Masarotto
Keyword(s):  
Control Charts ◽  
Estimated Parameters

Run-Length Performance of Regression Control Charts with Estimated Parameters

2004 ◽  
Vol 36 (3) ◽  
pp. 280-292 ◽  
Author(s):  
Lianjie Shu ◽  
Fugee Tsung ◽  
Kwok-Leung Tsui
Keyword(s):  
Control Charts ◽  
Run Length ◽  
Estimated Parameters ◽  
Regression Control

scholarly journals Design and Analysis of Control Charts for Standard Deviation with Estimated Parameters

2011 ◽  
Vol 43 (4) ◽  
pp. 307-333 ◽  
Author(s):  
Marit Schoonhoven ◽  
Muhammad Riaz ◽  
Ronald J. M. M. Does
Keyword(s):  
Standard Deviation ◽  
Control Charts ◽  
Estimated Parameters

ARL1 of the Attribute c Control Chart with Estimated Parameter

2015 ◽  
Vol 22 (02) ◽  
pp. 1550009 ◽  
Author(s):  
Teodor Tiplica
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Average Run Length ◽  
Computational Results ◽  
Run Length ◽  
Estimated Parameters ◽  
Starting Point ◽  
Polynomial Expression ◽  
Discrete Nature ◽  
Good Starting Point

In this paper, the out of control average run length (ARL1) of the c control chart with estimated parameter is computed for various shifts in the average number of nonconformities. In spite of the discrete nature of this chart, it is proved that a target in-control average run length (ARL0) can be obtained when the average number of nonconformities is estimated. This is a good starting point for comparing the performances of the c control chart with those of other attribute control charts with estimated parameters. Based on the computational results obtained, it is showed that the ARL1 of the c control chart with estimated parameter can be approximated by using a polynomial expression.

DESIGN OF THE c AND np CHARTS WHEN THE PARAMETERS ARE ESTIMATED

2012 ◽  
Vol 19 (02) ◽  
pp. 1250010 ◽  
Author(s):  
PHILIPPE CASTAGLIOLA ◽  
SHU WU
Keyword(s):  
Phase I ◽  
Process Parameters ◽  
Control Charts ◽  
Data Set ◽  
Estimated Parameters ◽  
Parameter Case

The performance of attribute control charts is usually evaluated under the assumption of known process parameters (i.e., the nominal proportion of nonconforming units or the nominal number of nonconformities). However, in practice, these process parameters are rarely known and have to be estimated from an in-control historical Phase I data set. In this paper, we investigate the number m of Phase I samples that would be necessary for the c and p charts with estimated parameters in order to obtain similar in-control ARL's as in the known parameters case. We also propose new specific chart parameters that allow the c and np charts with estimated parameters to have approximately the same in-control ARL's as the ones obtained in the known parameter case.

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