The effect of measurement errors on the performance of the homogenously weighted moving average X ¯ monitoring scheme

Monitoring schemes are typically designed under the assumption of perfect measurements. However, in real-life applications, data tend to be subjected to measurement errors, that is, a difference be...

[1]  Karl-Heinz Waldmann,et al.  Design of double CUSUM quality control schemes , 1996 .

[2]  Jean-Claude Malela-Majika,et al.  New distribution-free memory-type control charts based on the Wilcoxon rank-sum statistic , 2020 .

[3]  Olatunde A. Adeoti,et al.  On control chart for monitoring exponentially distributed quality characteristic , 2020, Trans. Inst. Meas. Control.

[4]  Muhammad Hanif,et al.  Performance of maximum EWMA control chart in the presence of measurement error using auxiliary information , 2020, Commun. Stat. Simul. Comput..

[5]  Muhammad Noor-ul-Amin,et al.  Auxiliary Information Based Mixed EWMA–CUSUM Mean Control Chart with Measurement Error , 2019, Iranian Journal of Science and Technology, Transactions A: Science.

[6]  Giovanna Capizzi,et al.  Combined Shewhart–EWMA control charts with estimated parameters , 2010 .

[7]  Muhammad Riaz,et al.  A mixed HWMA‐CUSUM mean chart with an application to manufacturing process , 2020, Qual. Reliab. Eng. Int..

[8]  Cédric Heuchenne,et al.  On the performance of CUSUM control charts for monitoring the coefficient of variation with measurement errors , 2019, The International Journal of Advanced Manufacturing Technology.

[9]  Muhammad Riaz,et al.  Mixed Exponentially Weighted Moving Average–Cumulative Sum Charts for Process Monitoring , 2013, Qual. Reliab. Eng. Int..

[10]  Nasir Abbas,et al.  On the Efficient Monitoring of Multivariate Processes with Unknown Parameters , 2020, Mathematics.

[11]  William H. Woodall,et al.  Effect of Measurement Error on Shewhart Control Charts , 2001 .

[12]  Tahir Nawaz,et al.  On Designing Distribution-Free Homogeneously Weighted Moving Average Control Charts , 2019, Journal of Testing and Evaluation.

[13]  Saddam Akber Abbasi,et al.  A Multivariate Homogeneously Weighted Moving Average Control Chart , 2019, IEEE Access.

[14]  Michael B. C. Khoo,et al.  The coefficient of variation chart with measurement error , 2017 .

[15]  Seyed Taghi Akhavan Niaki,et al.  Remedial Measures to Lessen the Effect of Imprecise Measurement with Linearly Increasing Variance on the Performance of the MAX-EWMAMS Scheme , 2018 .

[16]  Philippe Castagliola,et al.  The performance of the adaptive EWMA median chart in the presence of measurement error , 2018, Qual. Reliab. Eng. Int..

[17]  Matthew D. M. Pawley,et al.  Efficient Homogeneously Weighted Moving Average Chart for Monitoring Process Mean Using an Auxiliary Variable , 2019, IEEE Access.

[18]  Abdul Haq,et al.  New memory‐type dispersion control charts , 2017, Qual. Reliab. Eng. Int..

[19]  Jennifer Brown,et al.  New Synthetic EWMA and Synthetic CUSUM Control Charts for Monitoring the Process Mean , 2016, Qual. Reliab. Eng. Int..

[20]  Philippe Castagliola,et al.  Optimal performance of the variable sample sizes Hotelling’s T2 control chart in the presence of measurement errors , 2018, Quality Technology & Quantitative Management.

[21]  Nasir Abbas,et al.  Homogeneously weighted moving average control chart with an application in substrate manufacturing process , 2018, Comput. Ind. Eng..

[22]  Philippe Castagliola,et al.  Measurement errors in statistical process monitoring: A literature review , 2017, Comput. Ind. Eng..

[23]  Narayanaswamy Balakrishnan,et al.  On the performance of coefficient of variation charts in the presence of measurement errors , 2018, Qual. Reliab. Eng. Int..

[24]  Kim Phuc Tran,et al.  On the performance of VSI Shewhart control chart for monitoring the coefficient of variation in the presence of measurement errors , 2019, The International Journal of Advanced Manufacturing Technology.

[25]  A. Kouadri,et al.  An improved plant‐wide fault detection scheme based on PCA and adaptive threshold for reliable process monitoring: Application on the new revised model of Tennessee Eastman process , 2018 .

[26]  Philippe Castagliola,et al.  The new synthetic and runs-rules schemes to monitor the process mean of autocorrelated observations with measurement errors , 2020, Communications in Statistics - Theory and Methods.

[27]  Abdaljbbar B. A. Dawod,et al.  Efficient linear profile schemes for monitoring bivariate correlated processes with applications in the pharmaceutical industry , 2020 .

[28]  Muhammad Noor-ul-Amin,et al.  Hybrid Exponentially Weighted Moving Average Control Chart with Measurement Error , 2020 .

[29]  Philippe Castagliola,et al.  A variable parameters multivariate control chart for simultaneous monitoring of the process mean and variability with measurement errors , 2020, Qual. Reliab. Eng. Int..

[30]  Fu-Kwun Wang,et al.  VSSI median control chart with estimated parameters and measurement errors , 2018, Qual. Reliab. Eng. Int..

[31]  Saddam Akber Abbasi,et al.  Exponentially Weighted Moving Average Chart and Two‐Component Measurement Error , 2016, Qual. Reliab. Eng. Int..

[32]  Christos Koukouvinos,et al.  The triple exponentially weighted moving average control chart , 2020 .

[33]  S. C. Shongwe,et al.  A combined mixed-s-skip sampling strategy to reduce the effect of autocorrelation on the X̄ scheme with and without measurement errors , 2020, Journal of applied statistics.

[34]  Philippe Castagliola,et al.  Performance of the hotelling T2 control chart for compositional data in the presence of measurement errors , 2019, Journal of Applied Statistics.

[35]  Laith M. Halabi,et al.  Nonparametric Kullback-divergence-PCA for intelligent mismatch detection and power quality monitoring in grid-connected rooftop PV , 2019 .

[36]  Wahiba Bounoua,et al.  Online monitoring scheme using principal component analysis through Kullback-Leibler divergence analysis technique for fault detection , 2019, Trans. Inst. Meas. Control.

[37]  Hafiz Zafar Nazir,et al.  A double homogeneously weighted moving average control chart for monitoring of the process mean , 2020, Qual. Reliab. Eng. Int..

[38]  Philippe Castagliola,et al.  On monitoring the process mean of autocorrelated observations with measurement errors using the w‐of‐w runs‐rules scheme , 2020, Qual. Reliab. Eng. Int..

[39]  Olatunde Adebayo Adeoti,et al.  A hybrid homogeneously weighted moving average control chart for process monitoring , 2020, Qual. Reliab. Eng. Int..

[40]  Petros E. Maravelakis,et al.  Measurement error effect on the CUSUM control chart , 2012 .

[41]  Philippe Castagliola,et al.  Performance of the MEWMA‐CoDa control chart in the presence of measurement errors , 2020, Qual. Reliab. Eng. Int..

[42]  Dong Han,et al.  Monitoring the process location by using new ranked set sampling-based memory control charts , 2020 .

[43]  Mohammad Reza Soltanpour,et al.  Robust linear parameter varying attitude control of a quadrotor unmanned aerial vehicle with state constraints and input saturation subject to wind disturbance , 2020, Trans. Inst. Meas. Control.

[44]  Kim Phuc Tran,et al.  Design of a variable sampling interval exponentially weighted moving average median control chart in presence of measurement errors , 2021, Qual. Reliab. Eng. Int..

[45]  Phuong Hanh Tran,et al.  A Synthetic median control chart for monitoring the process mean with measurement errors , 2019, Qual. Reliab. Eng. Int..

[46]  Stelios Psarakis,et al.  EWMA Chart and Measurement Error , 2004 .

[47]  E. S. Page.  Cumulative Sum Charts , 1961 .