Distribution-free hybrid schemes for process surveillance with application in monitoring chlorine content of water

Sanusi, Ridwan A.; Chong, Zhi Lin; Mukherjee, Amitava; Xie, Min

doi:10.1016/j.chemolab.2020.104099

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…5. If the chart's statistic (in step 4) falls below the limit (in step 3), the process is declared to be IC, then repeats steps (1)(2)(3)(4) for the monitoring of the next test sample 𝑖 + 1. Alternatively, if the test statistic falls outside the limit, the process is said to have shifted to an OOC state.…”

Section: Performance Assessmentsmentioning

confidence: 99%

“…Walter A. Shewhart initially proposed the control charts in 1924 for process or product improvements. Since then, control charts have become standard methods for achieving process stability, improvement, and guidance in differentiating between natural and unnatural process or product variations in different service and manufacturing industries 1, 2. Their attractiveness is driven by the simplicity of their implementation, interpretation, and prompt detection of sudden and steady changes in the process parameters.…”

Section: Introductionmentioning

confidence: 99%

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Directionally sensitive homogeneously weighted moving average control charts

Adegoke

Ganiyu²

2021

Quality & Reliability Eng

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One‐sided control charts for monitoring changes in the mean level are proposed in this paper. The proposed charts are given in the form of a homogeneously weighted moving average technique that provides efficient monitoring of small shifts in the mean level. The charts accumulate observations that are above the target (or mean value) and truncated the observations that are less than the target to the target value in their computations. Average run length comparisons of the proposed charts with the existing one‐sided charts, based on the exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts, show that the proposed charts are more efficient in detecting small shifts than the competing charts. We investigate the sensitivity of the charts to non‐normality and show how they can be designed to be robust to non‐normal distributions. We provide a step‐by‐step implementation of the proposed charts when their parameters are unknown and estimated from historical reference data sets. The advantage of the proposed charts over some existing one‐sided charts is demonstrated via an illustrative example, involving monitoring mean lethal concentration (LC50) from a k‐nearest neighbours (KNN) regression‐based Quantitative Structure‐Activity Relationships (QSAR) model that relates LC50 to eight molecular descriptors.

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Section: Performance Assessmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Directionally sensitive homogeneously weighted moving average control charts

Adegoke

Ganiyu²

2021

Quality & Reliability Eng

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Proposed nonparametric runs rules Lepage and synthetic Lepage schemes

Chong

Mukherjee

Khoo

2022

Computers & Industrial Engineering

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Optimal design of the side sensitive group runs double sampling (SSGRDS) X¯ scheme with estimated process parameters

Chong,

Yeong,

Khaw

et al. 2024

Transactions of the Institute of Measurement and Control

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The side sensitive group runs double sampling (SSGRDS) [Formula: see text] scheme is previously studied under the known process parameters (Case-K) assumption. As the process parameters are hardly known in practical situations, they must be estimated using a suitably chosen in-control (IC) Phase-I sample. However, various studies demonstrated that a substantial amount of Phase-I sample is necessary so that the scheme with unknown process parameters (Case-U) attains a performance almost similar to that of the Case-K counterpart. Since it is challenging to acquire a vast number of IC samples, we examine the optimal designs of the Case-U SSGRDS [Formula: see text] scheme such that the average number of observations to signal (ANOS) and expected ANOS (EANOS) are minimised. The optimal parameters obtained for the Case-U SSGRDS [Formula: see text] scheme enable it to have a performance comparable to that of the Case-K counterpart, without the need for a large number of Phase-I samples. We show that the Case-U SSGRDS [Formula: see text] scheme is effective in identifying the process mean shift of a silicon epitaxial process.

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Distribution-free hybrid schemes for process surveillance with application in monitoring chlorine content of water

Cited by 3 publications

References 35 publications

Directionally sensitive homogeneously weighted moving average control charts

Directionally sensitive homogeneously weighted moving average control charts

Proposed nonparametric runs rules Lepage and synthetic Lepage schemes

Optimal design of the side sensitive group runs double sampling (SSGRDS) X¯ scheme with estimated process parameters

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