Assessment of Shewhart Control Chart Limits in Phase I Implementations Under Various Shift and Contamination Scenarios

Testik, Murat Caner; Weiß, Christian; Koca, Yesim; Testik, Özlem Müge

doi:10.1007/978-3-319-75295-2_2

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…This is useful especially for detecting process changes. Testik et al considered the snapshot approach of sampling for evaluating the effectiveness of phase I studies and concluded that a value of 3 for L is a reasonable choice as recommended in many textbooks. The random sampling approach is the case where units produced during a sampling interval are randomly selected and assigned to a subgroup to make decisions over a fixed period.…”

Section: Simulations Of Phase I Control Charts and Performance Metricsmentioning

confidence: 99%

Effectiveness of phase I applications for identifying randomly scattered out‐of‐control observations and estimating control chart parameters

Testik

Weiß

Koca

et al. 2017

Quality & Reliability Eng

Self Cite

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Estimation of unknown process parameters with fixed-size samples are studied in the following. The standard textbook approach for phase I control chart implementation with a Shewhart control chart is evaluated for the case of normally distributed independent observations with random sampling. The x−s charts are simultaneously implemented by generating observations that have a given percentage of randomly scattered out-of-control observations. Simulating the phase I steps, where out-of-control samples are detected iteratively by determining trial control limits, identifying samples exceeding these limits, and revising the control limits, the standard practice is evaluated in terms of both detection performance and quality of parameter estimates. It is shown that standard phase I control chart implementations with 3-σ-limits may perform very poorly in identifying true out-of-control observations and providing a reference set of in-control observations for estimation in some practical settings. A chart design with 2-σ-limits is recommended for a successful phase I analysis.

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Section: Simulations Of Phase I Control Charts and Performance Metricsmentioning

confidence: 99%

Effectiveness of phase I applications for identifying randomly scattered out‐of‐control observations and estimating control chart parameters

Testik

Weiß

Koca

et al. 2017

Quality & Reliability Eng

Self Cite

View full text Add to dashboard Cite

show abstract

Effect of contaminated phase I data on the phase II – EWMA control chart performance under non-normality

Saleh

Aly

Mahmoud

2022

Communications in Statistics - Simulation and Computation

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Guidelines for automating Phase I of control charts by considering effects on Phase-II performance of individuals control chart

Atalay

Testik

Duran

et al. 2019

Quality Engineering

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Assessment of Shewhart Control Chart Limits in Phase I Implementations Under Various Shift and Contamination Scenarios

Cited by 3 publications

References 15 publications

Effectiveness of phase I applications for identifying randomly scattered out‐of‐control observations and estimating control chart parameters

Effectiveness of phase I applications for identifying randomly scattered out‐of‐control observations and estimating control chart parameters

Effect of contaminated phase I data on the phase II – EWMA control chart performance under non-normality

Guidelines for automating Phase I of control charts by considering effects on Phase-II performance of individuals control chart

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