An economic approach towards using individual measurements to control the mean of continuously monitored processes

Sheil, J.

doi:10.1080/00207549508904856

Cited by 2 publications

(1 citation statement)

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“…The Shewhart charts may still be applicable to non-normal situations when the sample size is large as guaranteed by the Central Limit Theorem. However, in modern manufacturing environment, items are often checked one by one and control charts for individual measurements are desirable, see e.g., Sheil (1995), Gong et al (1997) and Xie et al (1998). The normality assumption for individual value is usually questionable and the normality should be tested before the implementation of traditional technique.…”

Section: Introductionmentioning

confidence: 99%

Process monitoring of exponentially distributed characteristics through an optimal normalizing transformation

Yang

Xie

2000

Journal of Applied Statistics

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Many process characteristics follow exponential distribution and control charts based on such a distribution have attracted a lot of attention. Traditional control limits may be not appropriate because of the lack of symmetry. In this paper, process monitoring through a normalizing power transformation is studied. The traditional individual measurements control charts can be used based on the transformed data. The properties of this control chart are investigated. Comparison with the chart using probability limits is also carried out for the cases of known and estimated parameter.Without losing much accuracy even compared with the exact probability limits, the power transformation approach can easily be used to produce charts that can be interpreted when the normality assumption is valid.

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Section: Introductionmentioning

confidence: 99%