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EWMA p charts under sampling by variables
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DOI：10.1080/00207543.2012.746799.png)
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摘要
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When it comes to manufacturing processes, the question of process quality is omnipresent. Statistical methods for monitoring quality measures are widespread and control charts are well established. Instead of checking parameters such as mu and sigma, there are control charts to monitor the percent defective . While control charts under sampling by attributes are already illustrated in the literature, this paper develops and modifies different approaches of control charts for under sampling by variables. The results for a modified exponentially moving average chart, EWMA , are compared to those of several control charts. The new scheme is well suited for imperfect in-control situations, that is, the pre-run sample mean differs from a certain natural or target mean value of the monitored parameter. To calculate the most popular control chart performance measure, the average run length (), both the Markov chain approach and the collocation method are used. It turns out that the EWMA chart has properties similar to the usual EWMA (X) over bar and the CUSUM (X) over bar charts. Thus, it can be a helpful utility for practical applications.
Keyword:
SPC
yield management
applied statistics
production control
percent defective
imperfect in-control state
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IF:
7.3
论文数:
1.1W
被引数:
3.7W
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