Exponentially Weighted Moving Average (EWMA) control charts are proposed to monitor ambient ozone (O3) levels in the city center and industrial areas of Muscat. Weekly averages of 8-hourly concentrations of ozone over a period of one year were used. The EWMA charts showed significant shift in the mean ozone levels at both the sites. However, both the ozone series were found to have significant autocorrelation. Therefore Box-Jenkins autoregressive integrated moving average (ARIMA) models were fitted at the first stage and then residuals were taken to apply EWMA which revealed that the ozone levels in both areas are within natural tolerance limits as well as within the international standard limit.
Published in | American Journal of Theoretical and Applied Statistics (Volume 4, Issue 4) |
DOI | 10.11648/j.ajtas.20150404.14 |
Page(s) | 254-257 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
ARIMA, EWMA, Quality Control Charts
[1] | Ahmad, M. I. Altobi, A.I. and Alsaadi, M.S. Monitoring Air Quality By Statistical Control Charts.J. Sci. Technol MSU, V33, No.2, 2014. Pp 157-159. |
[2] | Charles J Corbett, Jen-Nan Pan, 2002. Evaluating environmental performance using statistical process control techniques: European Journal of Operational Research.139, 68-83. |
[3] | Su-Tsu Chen, Jeh-Nan Pan (2008) : Monitoring long-memory air quality data using ARFIMA model Environmetrics 2008; 19: 209–219. |
[4] | Su-Tsu Chen, Jeh-Nan Pan, 2006. 25th Annual National Conference on Managing Environmental Quality Systems: Monitoring the Long-Memory Air Quality Data Using AFRIMA model. 831-70101. |
[5] | Montgomery, D.C, 2005. Introduction to Statistical Quality Control, 5rd ed.Wiley, New York. |
[6] | Bruce L. Bowerman & Richard T. O’Connell(2010) Forecasting and Time Series and applied approach, 5th Edition, Miami University. |
[7] | Kevin W. Bowman (2013) Toward the next generation of air quality monitoring: Ozone, Atmospheric Environment, Volume 80, December 2013, Pages 571–583. |
[8] | M. Omidvaria,b, S. Hassanzadeha,_, F. Hosseinibalama (2008). Time series analysis of ozone data in Isfahan. Physica A 387 (2008) 4393–4403. |
[9] | Jangho Park and Chi-Hyuck Jun (2015). A new multivariate EWMA control chart via multiple testing, Journal of Process Control, Volume 26, February 2015, Pages 51–55. |
[10] | HOLGER KRAMER and WOLFGANG SCHMID(1997) CONTROL CHARTS FOR TIME SERIES. Nonlinear Analysis, Theory, Methods & Applications, Vol. 30, No. 7. pp. 4007-4016. 1997 Proc. 2nd World Congress of Nonlinear Analysts. 1997 Elsevier Science Ltd. |
APA Style
Muhammad Idrees Ahmad. (2015). Exponentially Weighted Moving Average Control Charts for Monitoring Ambient Ozone Levels in Muscat. American Journal of Theoretical and Applied Statistics, 4(4), 254-257. https://doi.org/10.11648/j.ajtas.20150404.14
ACS Style
Muhammad Idrees Ahmad. Exponentially Weighted Moving Average Control Charts for Monitoring Ambient Ozone Levels in Muscat. Am. J. Theor. Appl. Stat. 2015, 4(4), 254-257. doi: 10.11648/j.ajtas.20150404.14
AMA Style
Muhammad Idrees Ahmad. Exponentially Weighted Moving Average Control Charts for Monitoring Ambient Ozone Levels in Muscat. Am J Theor Appl Stat. 2015;4(4):254-257. doi: 10.11648/j.ajtas.20150404.14
@article{10.11648/j.ajtas.20150404.14, author = {Muhammad Idrees Ahmad}, title = {Exponentially Weighted Moving Average Control Charts for Monitoring Ambient Ozone Levels in Muscat}, journal = {American Journal of Theoretical and Applied Statistics}, volume = {4}, number = {4}, pages = {254-257}, doi = {10.11648/j.ajtas.20150404.14}, url = {https://doi.org/10.11648/j.ajtas.20150404.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150404.14}, abstract = {Exponentially Weighted Moving Average (EWMA) control charts are proposed to monitor ambient ozone (O3) levels in the city center and industrial areas of Muscat. Weekly averages of 8-hourly concentrations of ozone over a period of one year were used. The EWMA charts showed significant shift in the mean ozone levels at both the sites. However, both the ozone series were found to have significant autocorrelation. Therefore Box-Jenkins autoregressive integrated moving average (ARIMA) models were fitted at the first stage and then residuals were taken to apply EWMA which revealed that the ozone levels in both areas are within natural tolerance limits as well as within the international standard limit.}, year = {2015} }
TY - JOUR T1 - Exponentially Weighted Moving Average Control Charts for Monitoring Ambient Ozone Levels in Muscat AU - Muhammad Idrees Ahmad Y1 - 2015/06/02 PY - 2015 N1 - https://doi.org/10.11648/j.ajtas.20150404.14 DO - 10.11648/j.ajtas.20150404.14 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 254 EP - 257 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20150404.14 AB - Exponentially Weighted Moving Average (EWMA) control charts are proposed to monitor ambient ozone (O3) levels in the city center and industrial areas of Muscat. Weekly averages of 8-hourly concentrations of ozone over a period of one year were used. The EWMA charts showed significant shift in the mean ozone levels at both the sites. However, both the ozone series were found to have significant autocorrelation. Therefore Box-Jenkins autoregressive integrated moving average (ARIMA) models were fitted at the first stage and then residuals were taken to apply EWMA which revealed that the ozone levels in both areas are within natural tolerance limits as well as within the international standard limit. VL - 4 IS - 4 ER -