Capability index-based control chart for monitoring process mean using repetitive sampling

Adeoti, Olatunde Adebayo; Olaomi, John Olutunji

doi:10.1080/03610926.2017.1307401

Cited by 21 publications

(7 citation statements)

References 25 publications

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“…Repetitive sampling plans based on one-sided specifications limits were presented by Yen et al [17] Recently, Saghir et al [10] developed a repetitive control chart for exponentially weighted moving average (EWMA) statistic using auxiliary information for monitoring process means. During the last few years, repetitive sampling has been explored by many authors including Adeoti and Olaomi [18], Aslam et al [19], Aslam et al [19], Aslam et al [20], Balamurali and Jun [14], Balamurali et al [13], Jun et al [21], Liu and Wu [22], and Radhakrishnan and Sivakumaran [23].…”

Section: Introductionmentioning

confidence: 99%

Process Monitoring for Gamma Distributed Product under Neutrosophic Statistics Using Resampling Scheme

Almarashi

Aslam

2021

Journal of Mathematics

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In this article, a repetitive sampling control chart for the gamma distribution under the indeterminate environment has been presented. The control chart coefficients, probability of in-control, probability of out-of-control, and average run lengths have been determined under the assumption of the symmetrical property of the normal distribution using the neutrosophic interval method. The performance of the designed chart has been evaluated using the average run length measurements under different process settings for an indeterminate environment. In-control and out-of-control nature of the proposed chart under different levels of shifts have been described. The comparison of the proposed chart has been made with the existing chart. A real-world example from the healthcare department has been included for the practical application of the proposed chart. It has been observed from the simulation study and real example that the proposed control chart is efficient in quick monitoring of the out-of-control process. It can be concluded that the proposed control chart can be applied effectively in uncertainty.

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Section: Introductionmentioning

confidence: 99%

Process Monitoring for Gamma Distributed Product under Neutrosophic Statistics Using Resampling Scheme

Almarashi

Aslam

2021

Journal of Mathematics

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“…However, their approaches was based on the range statistic that losses its statistical efficiency when estimating standard deviation for large sample sizes and inappropriate with non-normal distribution (Montgomery, 2009). Adeoti & Olaomi (2018) proposed a repetitive sampling PCI-based control chart using an unbiased estimator ̂ ̅ for monitoring process stability and process capability where…”

Section: Matter: International Journal Of Science and Technology Issn 2454-5880mentioning

confidence: 99%

A New Control Chart for Process Monitoring Based on the Unified Capability Index

Adeoti

2020

mijst

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Control charts based on capability index for monitoring process parameters have received wide attention recently. In this paper, we proposed new control charts for online monitoring of the process mean and variability using a unified capability index approach. Control chart coefficients are given for constructing the unified capability index-based mean ( ̅ ) and standard deviation (S) control charts. Real life data is given to demonstrate the advantages of the proposed control charts over the standard mean ( ̅ ) and standard deviation (S) charts for process monitoring. The results of study showed that the proposed unified capability index-based control charts outperform the standard ̅ and S control charts and it is efficient for simultaneous monitoring of process stability and measuring the capability of the process to meet specification.

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“…Example II (real-life data) The measurement of the flow width of the photoresist material applied to a silicon wafer in a hard-bake process used in conjunction with photolithography in semiconductor manufacturing taken from the study of Montgomery (2009) is considered. The first 25 samples with each of five wafers were collected when the process is in-control and the last 20 samples were collected when the process shifts has occur resulting in an out-of-control situation (Adeoti and Olaomi, 2018).…”

Section: Illustrative Examplesmentioning

confidence: 99%

A new double exponentially weighted moving average control chart using repetitive sampling

Adeoti

2018

IJQRM

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Purpose The purpose of this paper is to propose a double exponentially weighted moving average control chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the efficiency of detecting small process mean shift. Design/methodology/approach The algorithm for the implementation of the proposed chart is developed and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs are presented for various process mean shift. The performance of the proposed chart is investigated in terms of the average run-length for small process mean shift and compared with the existing DEWMA control chart. Numerical examples are given as illustration of the design and implementation of the proposed chart. Findings The proposed control chart is more efficient than the existing DEWMA control chart in the detection of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift. However, the performance of the proposed chart relatively deteriorates for large smoothing constants. Practical implications The application of repetitive sampling in the control chart literature is gaining wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in the detection of small process mean shift by process control personnel. Originality/value This paper fills a gap in the literature by examining the performance of the repetitive sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in the literature, however, its use based on the DEWMA statistic has not been considered in this context.

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Capability index-based control chart for monitoring process mean using repetitive sampling

Cited by 21 publications

References 25 publications

Process Monitoring for Gamma Distributed Product under Neutrosophic Statistics Using Resampling Scheme

Process Monitoring for Gamma Distributed Product under Neutrosophic Statistics Using Resampling Scheme

A New Control Chart for Process Monitoring Based on the Unified Capability Index

A new double exponentially weighted moving average control chart using repetitive sampling

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