scholarly journals KURTOSIS CORRECTION METHOD FOR VARIABLE CONTROL CHARTS - A COMPARISON IN LAPLACE DISTRIBUTION

2010 ◽  
Vol 7 (1) ◽  
pp. 51
Author(s):  
Metlapalli Chaitanya Priya
Keyword(s):  
Control Charts ◽  
Correction Method ◽  
Laplace Distribution ◽  
Variable Control

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
Keyword(s):  
Control Charts ◽  
Gumbel Distribution ◽  
Variable Control

scholarly journals On Performance of Two-Parameter Gompertz-Based X¯ Control Charts

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Johnson A. Adewara ◽  
Kayode S. Adekeye ◽  
Olubisi L. Aako
Keyword(s):  
Control Chart ◽  
Coverage Probability ◽  
Control Charts ◽  
Average Run Length ◽  
Real Life ◽  
Correction Method ◽  
Gompertz Distribution ◽  
Real Life Data ◽  
Control Limits ◽  
Two Parameter

In this paper, two methods of control chart were proposed to monitor the process based on the two-parameter Gompertz distribution. The proposed methods are the Gompertz Shewhart approach and Gompertz skewness correction method. A simulation study was conducted to compare the performance of the proposed chart with that of the skewness correction approach for various sample sizes. Furthermore, real-life data on thickness of paint on refrigerators which are nonnormal data that have attributes of a Gompertz distribution were used to illustrate the proposed control chart. The coverage probability (CP), control limit interval (CLI), and average run length (ARL) were used to measure the performance of the two methods. It was found that the Gompertz exact method where the control limits are calculated through the percentiles of the underline distribution has the highest coverage probability, while the Gompertz Shewhart approach and Gompertz skewness correction method have the least CLI and ARL. Hence, the two-parameter Gompertz-based methods would detect out-of-control faster for Gompertz-based X¯ charts.

Designing variable control charts under failure censoring reliability tests with replacement

2020 ◽  
Vol 42 (15) ◽  
pp. 3002-3011
Author(s):  
Hasan Rasay ◽  
Hossein Arshad
Keyword(s):  
Control Charts ◽  
Type I Error ◽  
Average Run Length ◽  
Quality Characteristic ◽  
Erlang Distribution ◽  
Type I ◽  
Chi Square ◽  
Variable Control ◽  
Specific Distribution ◽  
The One

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.

scholarly journals CONTRIBUTION TO THE SPC IMPLEMENTATION BY SELECTING AN APPROPRIATE VARIABLE CONTROL CHART

2021 ◽  
Vol 24 (1) ◽  
pp. 50-54
Author(s):  
Mite Tomov ◽  
◽  
Leonard Abazovski ◽  
Anastasija Ignjatovska ◽  
◽  
...  
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Mean Value ◽  
Practical Implementation ◽  
Statistical Process ◽  
Serial Production ◽  
Variable Control ◽  
Percentage Difference ◽  
The Mean ◽  
Distribution Type

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.

VARIABLE CONTROL CHARTS BASED ON PARETO – RAYLEIGH DISTRIBUTION

2019 ◽  
Vol 8 (4) ◽  
pp. 32
Author(s):  
RAO I. NARASIMHA ◽  
M. S. RAVIKUMAR ◽  
KANTAM R. R. L. ◽  
◽  
◽  
...  
Keyword(s):  
Control Charts ◽  
Rayleigh Distribution ◽  
Variable Control
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