Acceptance Control Charts Based on Normal Approximations to the Poisson Distribution

1981 ◽  
Vol 13 (4) ◽  
pp. 221-227 ◽  
Author(s):  
Suresh Mhatre ◽  
Richard L. Scheaffer ◽  
Richard S. Leavenworth
Keyword(s):  
Poisson Distribution ◽  
Control Charts ◽  
Normal Approximations ◽  
Acceptance Control

scholarly journals A Control Chart Based on Moving Average Model Functioned for Poisson Distribution

2020 ◽  
Vol 3 (10) ◽  
Author(s):  
Hira Arooj ◽  
◽  
Khawar Iqbal Malik ◽  
Keyword(s):  
Poisson Distribution ◽  
Control Chart ◽  
Control Charts ◽  
Moving Average ◽  
Current Control ◽  
Average Model ◽  
Time Intervals ◽  
Manufacture Process ◽  
Moving Average Model

A control chart used with MA control chart to track the number of faulty products or faults suggested. When the characteristics of quality of interest obey a Poisson distribution. A specified number of objects are observed at various time intervals in order to observe the number of non-conformities. By measuring ARLs under different sample sizes and parameters by considering ARLs in power, the output of the proposed chart is evaluated. It should be noted The proposed control chart seems to be morereliable than the traditional current control charts in detecting small adjustments in the manufacture process.

Attribute control charts using generalized zero-inflated Poisson distribution

2008 ◽  
Vol 24 (7) ◽  
pp. 793-806 ◽  
Author(s):  
Nan Chen ◽  
Shiyu Zhou ◽  
Tzyy-Shuh Chang ◽  
Howard Huang
Keyword(s):  
Poisson Distribution ◽  
Control Charts ◽  
Generalized Zero

Acceptance control charts for non-normal data

2005 ◽  
Vol 32 (1) ◽  
pp. 25-36 ◽  
Author(s):  
Chao-Yu Chou ◽  
CHung-Ho Chen ◽  
Hui-Rong Liu
Keyword(s):  
Control Charts ◽  
Acceptance Control

A hybrid exponentially weighted moving average chart for COM-Poisson distribution

2016 ◽  
Vol 40 (2) ◽  
pp. 456-461 ◽  
Author(s):  
Muhammad Aslam ◽  
Nasrullah Khan ◽  
Chi-Hyuck Jun
Keyword(s):  
New York ◽  
Poisson Distribution ◽  
Control Chart ◽  
Control Charts ◽  
Moving Average ◽  
Statistical Quality Control ◽  
Exponentially Weighted Moving Average ◽  
Run Lengths ◽  
Weighted Moving Average ◽  
Exponentially Weighted

We provide the complete design of a hybrid exponentially weighted moving average (HEWMA) control chart for COM-Poisson distribution. The necessary measures of the proposed control chart are given in this manuscript, and the average run lengths (ARLs) are determined through Monte Carlo simulation for various values of specified parameters. The performance of the proposed chart is compared with two existing control charts. The proposed chart is more efficient than these two existing charts in terms of ARLs; application of the proposed chart is described with the help of Montgomery’s data ( Introduction to Statistical Quality Control, John Wiley & Sons, New York, 2007).

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