Variable Control Charts for Gumbel Distribution Based on Percentiles

2018 ◽  
Vol 9 (12) ◽  
pp. 1890-1897
Author(s):  
K. Rosaiah ◽  
B. Srinivasa Rao ◽  
J. Pratapa Reddy ◽  
C. Chinnamamba
2020 ◽  
Vol 42 (15) ◽  
pp. 3002-3011
Author(s):  
Hasan Rasay ◽  
Hossein Arshad

There exist many processes where the quality characteristic does not follow a normal distribution, and the conditions for the application of central limit theorem are not satisfied; for example, because collecting data in a subgroup is impossible or the distribution is highly skewed. Thus, researchers have developed the control charts according to the specific distribution that models the quality characteristic. In this paper, some control charts are designed to monitor an exponentially distributed lifetime. The life testing is conducted according to the failure censoring while during the test; once observing a failure item, it is replaced by a new one so that the total number of items inspected during the test remains constant. Under the condition of the test, it is discussed that the elapsed time until observing the r’th failure has Erlang distribution. According to the relation of Erlang and chi-square distributions, the chart limits are computed to satisfy a specified value of type I error. Examples are presented and the curves of average run length are derived for the one-sided and two-sided control charts. Also, a comparative study is conducted to show the performance and superiority of the proposed control charts.


2021 ◽  
Vol 24 (1) ◽  
pp. 50-54
Author(s):  
Mite Tomov ◽  
◽  
Leonard Abazovski ◽  
Anastasija Ignjatovska ◽  
◽  
...  

The research in this paper contributes to the practical implementation of the Statistical Process Control (SPC), primarily in the serial production by selecting an appropriate variable control chart. The paper proposes a procedure algorithm where the deciding criteria used to select the variable control chart include: the data distribution type (whether an approximately normal distribution or not), the number of elements in the subgroup (n) for grouped data, the shift size value and the percentage difference between the shift size value and the mean value of the shifts calculated for each subgroup. The paper explains the proposed algorithm using examples with appropriately drawn control charts, which algorithm essentially represents an extension of the algorithm presented in ISO 7870-2:2013.


2019 ◽  
Vol 8 (4) ◽  
pp. 32
Author(s):  
RAO I. NARASIMHA ◽  
M. S. RAVIKUMAR ◽  
KANTAM R. R. L. ◽  
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◽  
...  

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