Adaptive MEWMA charts for univariate and multivariate simple linear profiles

Abdul Haq

21 citations0/0 files storedCommunication in Statistics- Theory and Methods

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Advanced Statistical Process Monitoring Advanced Control Systems Optimization Fault Detection and Control Systems

Abstract

The adaptive multivariate EWMA (MEWMA) charts have been widely recognized as an efficient process monitoring tool because of their ability to quickly respond against the shift of various sizes. In this paper, an adaptive MEWMA (AMEWMA) chart is proposed for monitoring the simple linear profile. In addition, new MEWMA and AMEWMA charts are also proposed to monitor the multivariate simple linear profile. The run length characteristics of these control charts are computed using the Monte Carlo simulation method. A detailed comparative study is conducted to compare the detection abilities of the proposed and existing charts when detecting different shifts in the parameters of the univariate and multivariate simple linear profiles. It is found that the AMEWMA chart performs substantially better than the existing charts. An example is given to explain the implementation of the AMEWMA chart.

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References

1992Introduction to Statistical Quality Control 1959Control Chart Tests Based on Geometric Moving Averages 1992A Multivariate Exponentially Weighted Moving Average Control Chart 2000On-Line Monitoring When the Process Yields a Linear Profile 2004Using Control Charts to Monitor Process and Product Quality Profiles 2003On the Monitoring of Linear Profiles 2003An Adaptive Exponentially Weighted Moving Average Control Chart 2004Phase I Analysis of Linear Profiles With Calibration Applications

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2023An unbiased function‐based Poisson adaptive EWMA control chart for monitoring range of shifts 2023Monitoring simple linear profiles in the presence of within‐ and between‐profile autocorrelation 2022An adaptive multivariate EWMA mean chart with variable sample sizes and/or variable sampling intervals

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