The Performance of Max-GWMA Control Chart in the Presence of Measurement Errors

• Autorzy: Sharafi Saeid , Maleki Mohammad Reza , Salmasnia Ali , Mansoor Reihaneh

Identyfikatory

DOI

10.24425/mper.2022.142392

• Języki publikacji: EN

Abstrakty

EN

Recently, simultaneous monitoring of process mean and variability has gained increasing attention. By departing from the accurate measurements assumption, this paper investigates the effect of gauge measurement errors on the performance of the maximum generally weighted moving average (Max-GWMA) chart for simultaneous monitoring of process mean and variability under an additive covariate model. Multiple measurements procedure is employed to compensate for the undesired impact of gauge inaccuracy on detection capability of the MaxGWMA chart. Simulation experiments in terms of average run length (ARL) are conducted to assess the power of the developed chart to detect different out-of-control scenarios. The results confirm that the gauge inaccuracy affects the sensitivity of the Max-GWMA chart. Moreover, the results show that taking multiple measurements per item adequately decreases the adverse effect of measurement errors. Finally, a real-life example is presented to demonstrate how measurement errors increases the false alarm rate of the Max-GWMA chart.

Słowa kluczowe

EN

max-GWMA control chart; average run length; measurement errors; simultaneous monitoring; multiple measurements

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2022
• Tom: Vol. 13, No. 4
• Strony: 26--37
• Opis fizyczny: Bibliogr. 31 poz., tab., wykr.

Twórcy

autor

Sharafi Saeid

• Department of Industrial Engineering, Faculty of Engineering, University of Qom, Iran

autor

Maleki Mohammad Reza

• Industrial Engineering Group, Golpayegan College of Engineering, Isfahan University of Technology, Golpayegan, 87717-67498, Iran

autor

Salmasnia Ali

• Department of Industrial Engineering, Faculty of Engineering, University of Qom, Iran

autor

Mansoor Reihaneh

• Department of Industrial Engineering, University of Eyvanekey, Eyvanekey, Iran

Bibliografia

• Amiri A., Ghashghaei R. and Maleki, M.R. (2018), On the effect of measurement errors in simultaneous monitoring of mean vector and covariance matrix of multivariate processes, Transactions of the Institute of Measurement and Control, No. 1, Vol. 40, pp. 318–330.
• Asif F., Khan S. and Noor-ul-Amin, M. (2020), Hybrid Exponentially Weighted Moving Average Control Chart with Measurement Error, Iranian Journal of Science and Technology Transaction A-Science, Vol. 44, pp. 801–811.
• Chen G., Cheng S.W. and Xie H. (2001), Monitoring process mean and variability with one EWMA chart, Journal of Quality Technology, No. 2, Vol. 33, pp. 223–233.
• Cheng X.B. and Wang F.K. (2018), The performance of EWMA median and CUSUM median control charts for a normal process with measurement errors, Quality and Reliability Engineering International, No. 2, Vol. 34, pp. 203–213.
• Domangue R. and Patch S.C. (1991), Some omnibus exponentially weighted moving average statistical process monitoring schemes, Technometrics, No. 3, Vol. 33, pp. 299–313.
• Ghashghaei R., Bashiri M., Amiri A. and Maleki M.R. (2016), Effect of measurement error on joint monitoring of process mean and variability under ranked set sampling, Quality and Reliability Engineering International, No. 8, Vol. 32, pp. 3035–3050.
• Hawkins D.M. and Maboudou-Tchao E.M. (2008), Multivariate exponentially weighted moving covariance matrix, Technometrics, No. 2, Vol. 50, pp. 155–166.
• Khalafi S., Salmasnia A. and Maleki M.R. (2020), Remedial approaches to decrease the effect of measurement errors on simple linear profile monitoring, International Journal for Quality Research, No. 4, Vol. 14.
• Khati Dizabadi A., Shahrokhi M. and Maleki M.R. (2016), On the effect of measurement error with linearly increasing-type variance on simultaneous monitoring of process mean and variability, Quality and Reliability Engineering International, No. 5, Vol. 32, pp. 1693–1705.
• Linna K.W. and Woodall W.H. (2001), Effect of measurement error on Shewhart control charts, Journal of Quality Technology, No. 2, Vol. 33, pp. 213–222.
• Maleki M.R., Amiri A. and Castagliola P. (2017), Measurement errors in statistical process monitoring: A literature review, Computers & Industrial Engineering, Vol. 103, pp. 316–329.
• Maleki M.R. and Salmasnia A. (2017), Joint Monitoring of Process Location and Dispersion Based on CUSUM Procedure and Generalized Likelihood Ratio in the Presence of Measurement Errors, Quality and Reliability Engineering International, No. 7, Vol. 33, pp. 1485–1498.
• Maleki M.R., Shamseddin B., Eghbali H. and Bazda A. (2022a), The effect of gauge measurement errors on double sampling control chart. Communications in Statistics-XTheory and Methods, In Press. DOI: 10.1080/03610926.2021.1958848.
• Maleki M.R., Salmasnia A. and Yarmohammadi Saber S. (2022b), The Performance of Triple Sampling X Control Chart with Measurement Errors, Quality Technology & Quantitative Management, In Press. DOI: 10.1080/16843703.2022.2040702.
• Nguyen H.D., Nguyen Q.T., Nguyen T.H., Balakrishnan N., and Tran K.P. (2020a), The Performance of the EWMA Median Chart in the Presence of Measurement Error, Artificial Intelligence Evolution, pp. 48–62.
• Nguyen H.D., Tran K.P., Celano G., Maravelakis P.E. and Castagliola P. (2020b), On the effect of the measurement error on Shewhart t and EWMA t control charts, The International Journal of Advanced Manufacturing Technology, Vol. 107, pp. 4317–4332.
• Noor-ul-Amin M., Javaid A., Hanif M. and Dogu E. (2022), Performance of maximum EWMA control chart in the presence of measurement error using auxiliary information, Communications in Statistics-Simulation and Computation, In Press. DOI: 10.1080/03610918.2020.1772301.
• Quesenberry C.P. (1995), On properties of Q charts for variables, Journal of Quality Technology, No. 3, Vol. 27, pp. 184–203.
• Roberts S.W. (2000), Control chart tests based on geometric moving averages, Technometrics, No. 1, Vol. 42, pp. 97–101.
• Salmasnia A., Maleki M.R. and Niaki S.T.A. (2018a), Remedial measures to lessen the effect of imprecise measurement with linearly increasing variance on the performance of the MAX-EWMAMS scheme, Arabian Journal for Science and Engineering, No. 6, Vol. 43, pp. 3151–3162.
• Salmasnia A., Namdar M. and Noroozi M. (2018b), Robust design of a VP-NCS chart for joint monitoring mean and variability in series systems under maintenance policy, Computers & Industrial Engineering, Vol. 124, pp. 220–236.
• Sheu, S.H., and Griffith, W.S. (1996), Optimal number of minimal repairs before replacement of a system subject to shocks. Naval Research Logistics (NRL), No. 3, Vol. 43, 319–333.
• Sheu S.H., Huang C.J. and Hsu T.S. (2012), Extended maximum generally weighted moving average control chart for monitoring process mean and variability, Computers & Industrial Engineering, No. 1, Vol. 62, pp. 216–225.
• Sheu S.H. and Lin T.C. (2003), The generally weighted moving average control chart for detecting small shifts in the process mean, Quality Engineering, No. 2, Vol. 16, pp. 209–231.
• Sheu S.H. and Tai S.H. (2006), Generally weighted moving average control chart for monitoring process variability, The International Journal of Advanced Manufacturing Technology, No. 5–6, Vol. 30, pp. 452–458.
• Tang A., Castagliola P., Hu X. and Sun J. (2019), The performance of the adaptive EWMA median chart in the presence of measurement error, Quality and Reliability Engineering International, No. 1, Vol. 35, pp. 423–438.
• Tang A., Castagliola P., Sun J. and Hu X. (2018), The effect of measurement errors on the adaptive EWMA chart, Quality and Reliability Engineering International, No. 4, Vol. 34, pp. 609–630.
• Tran P.H., Tran K.P. and Rakitzis A. (2019), A synthetic median control chart for monitoring the process mean with measurement errors, Quality and Reliability Engineering International, No. 4, Vol. 35, pp. 1100–1116.
• Xie H. (1999), Contributions to qualimetry [PhD thesis]. Winnipeg, Canada: University of Manitoba.
• Yousefi S., Maleki M.R., Salmasnia A. and Anbohi M.K. (2022), Performance of multivariate homogeneously weighted moving average chart for monitoring the process mean in the presence of measurement errors, Journal of Advanced Manufacturing Systems, In Press, DOI: 10.1142/S0219686723500026.
• Zaidi F.S., Castagliola P., Tran K.P. and Khoo M.B.C. (2020), Performance of the MEWMA-CoDa control chart in the presence of measurement errors, Quality and Reliability Engineering International, No. 7, Vol. 36, pp. 2411–2440.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)