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Monitoring Poisson Observations Using Modified Exponentially Weighted Moving Average Control Charts

 

作者: F.F. Gan,  

 

期刊: Communications in Statistics - Simulation and Computation  (Taylor Available online 1990)
卷期: Volume 19, issue 1  

页码: 103-124

 

ISSN:0361-0918

 

年代: 1990

 

DOI:10.1080/03610919008812847

 

出版商: Marcel Dekker, Inc.

 

关键词: statistical process control (SPC);average run length (ARL);Markov chain;c-chart

 

数据来源: Taylor

 

摘要:

In certain production processes, it is necessary or more convenient to use counts of defects or conformance per unit of measurement to indicate whether a production process is in control or not. Counts of this kind are often well fitted by a Poisson distribution. Three modified exponentially weighted moving average (EWMA) control charts are developed in this paper for monitoring the Poisson counts. The average run length (ARL) and the probability function of the run length of these modified control charts can be computed exactly using results from the Markov Chain theory. These modified control charts are demonstrated to be generally superior than the Shewhart control chart based on ARL consideration. Tables of in-control ARLs of these modified control charts are given to assist the implementation of these modified control charts. The implementation and design of these EWMA control charts are discussed. The use of these modified EWMA control charts is illustrated with an example.

 

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