International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Aries Susanty*, M. Mujiya Ulkhaq, and Devi Amalia

Industrial Engineering Department, Diponegoro University, Campus Tembalang, Semarang


 

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ABSTRACT


This research aims to find the multivariate control chart which is suitable for production process, determine the current capability process, and also find the dominant variable which is correspondent to the improvement of drinking water quality. This research use a secondary data collected from January 2016 until February 2017. There were four group of variable used in this research. The first group was consist of color, turbidity, maximum containing level of copper and manganese. The second group consist of level of total dissolved solid, hardness, calcium and magnesium. The third level was consist of ph. value and alkaline; and fourth group consist of nitrate and nitrite. The result of data processing showed us that Multivariate Exponentially Weighted Moving Average or MEWMA control chart can detect the out of control data in the each group of variable faster than T2 Hotelling control chart. Then, the capability process index for the first group of variable is 2.238, the capability process index for second group of variable is 4.208, the capability process index for third group of variable is 1.438, and capability process index for fourth group of variable is 1.346. All group of variable have capability process index more than 1. This condition indicated that process goes well in all group of variable although there were some data is out of control in each group variable.


Keywords: Drinking water; multivariate control chart; group of variable; capability process index.


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REFERENCES


  1. [1] Tyagi, S., Sharma, B., Singh, P., and Dobhal, R. 2013. Water quality assessment in terms of water quality index. American Journal of Water Resources, 1, 3: 34-38. doi: 10.12691/ajwr-1-3-3

  2. [2] Miller, T. G. 1989. “Environmental Science: Working with the earth (2nd)”. Wadsworth Publishing Company, Belmont, California.

  3. [3] Jackson, R. B., Carpenter, S. R., Dahm, C. N., McKnight, D. M., Naiman, R. J., Postel, S. L., and Running, S. W. 2001. Water in a changing world. Ecological applications, 11, 4: 1027-1045.doi:10.1890/1051-0761(2001)011%5B1027:WIACW%5D2.0.CO;2

  4. [4] Krishnan, R. R., Dharmaraj, K., and Kumari, B. R. 2007. A comparative study on the physicochemical and bacterial analysis of drinking, borewell and sewage water in the three different places of Sivakasi. Journal of Environmental biology, 28, 1: 105-108.

  5. [5] Lowry, C. A., Woodall, W. H., Champ, C. W., and Rigdon, S. E. 1992. A multivariate exponentially weighted moving average control chart. Technometrics, 34, 1: 46-53. doi: 2307/1269551

  6. [6] Matrix, C., Reynolds Jr., M. R., and Cho, G.-Y. 2006. Multivariate control charts for monitoring the mean vector and covariance matrix. Journal of Quality Technology, 38, 3: 230-253. doi:10.1080/00224065.2006.11918612

  7. [7] Zou, C., and Tsung, F. 2011. A multivariate sign EWMA control chart. Technometrics, 53, 1: 84-97. doi: 1198/TECH.2010.09095

  8. [8] Li, Z., Zou, C., Wang, Z., and Huwang, L. 2013. A multivariate sign chart for monitoring process shape parameters. Journal of Quality Technology, 45, 2: 149-165. doi: 10.1080/00224065.2013.11917923

  9. [9] Mason, R. L., Tracy, N. D., and Young, J. C. 1997. A practical approach for interpreting multivariate T2 control chart signals. Journal of Quality Technology, 29, 4: 396-406. doi: 10.1080/00224065.1997.11979791

  10. [10] Hotelling, H. 1947. Multivariate quality control, illustrated by the air testing of sample bombsights. In Eisenhart, C., Hastay, M. W., and Wallis, W. A. (Ed.), Techniques of Statistical Analysis ( 111-184). McGraw Hill, New York.

  11. [11] Mason, R. L., Chou, Y.-M., and Young, J. C. 2008. Identifying variables contributing to outliers in phase I. Communications in Statistics—Theory and Methods, 37, 7: 1103-1118. doi: 10.1080/03610920701713245

  12. [12] Montgomery, D. C. 2009. “Introduction to Statistical Quality Control (6th)”. John Wiley & Sons., New York.

  13. [13] Kordi, M. G. and Ghufran, H. K”. 2005. “Marine Fish Cultivation in Floating Net Cages”. PT Rineka Cipta, Jakarta.

  14. [14] Arthana, I. W. 2007. The study of water quality of springs surrounding Bedugul, Bali. Journal of Environment (Bumi Lestari), 7, 1: 1-9. [in Indonesian]

  15. [15] Arinda, A., Mustafid, M., and Mukid, M. A. 2016. Penerapan diagram kontrol multivariabte exponentially weighted moving average (MEWMA) pada pengendalian karakteristik kualitas air (Studi kasus: Instalasi air III PDAM tirta moedal kota semarang). Jurnal Gaussian, 5, 1: 31-40. [in Indonesian]


ARTICLE INFORMATION


Received: 2018-06-29
Revised: 2018-10-10
Accepted: 2018-10-11
Available Online: 2018-10-11


Cite this article:

Susanty, A., Ulkhaq, M.M., Amalia, D. 2018. Using multivariate control chart to maintain the quality of drinking water in accordance with standard. International Journal of Applied Science and Engineering, 15, 83-94. https://doi.org/10.6703/IJASE.201810_15(2).083


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