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Application of Statistical Process Control in a Production Process

Received: 29 December 2015     Accepted: 6 January 2016     Published: 31 January 2016
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Abstract

This study evaluates the process of production of Champion Breweries Plc., located at Aka Offot, Uyo, Akwa Ibom State Nigeria. The information on the following measurable characteristics used during production were obtained; Brilliance (Haze), pH, Original Gravity (O.G) and Alcohol Percentage. Information on the number of defective crates recorded for the period of fifteen (15) days on Amstel Malta were also obtained from the bottling section. Mean (X ̅) and Range (R) control charts for variable were adopted to ascertain if the process with respect to each quality characteristics is statistically in control. The result shows that, the out-of-control points for BRILLANCE (B) were four (4) and one (1) out of twenty (20) for the mean and range charts respectively. For pH: two (2) and one (1) out of control for mean and range charts respectively. For Original Gravity (O.G): five and zero were out of control for mean and range charts respectively. For Alcohol Percentage (A): twelve and zero were out-of-control for mean and range charts respectively. Since the out-of-control points for Alcohol have exceeded the average of all points, the entire process is disregarded, and hence the process has to be overhauled. Using the P-chart to examine the defects in the finished produce daily for 15 days; it was found that 11 points were out of control, also the need for overhaul of the entire production line. Given the overall findings it could be deduced that the process was largely out-of-control, hence the need for total overhaul and the revised control schemes as appropriate. Thus, revised control schemes were formulated for the different quality characteristics for the process to be in control and the following control schemes were proposed for the future upper and lower specifications: B (X ̅: 0.6563, 0.2738; R: 0.4940, 0.00), pH (X ̅: 3.9786, 3.7916; R; 0.2871, 0.00).

Published in Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 1)
DOI 10.11648/j.sjams.20160401.11
Page(s) 1-11
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), 2016. Published by Science Publishing Group

Keywords

Statistical Quality Control (SQC), Statistical Process Control (SPC), Total Quality Management (TQM), Control Charts and Control Limits

References
[1] ALFORD, L. P. and BEATTY, H. R., (1951): Principles of Industrial Management: Rev. and Rewritten. Ronald Press Company. Ronald Press Co. New York.
[2] APPALASAMY, P., MUSTAPHA, A., RIZAL, N., JOHARI, F. and MANSOR, A. (2012): Classification-based Data Mining Approach for Quality Control in Wine Production; Journal of Applied Sciences, 12 (6) pp. 598-601.
[3] BREYFOGLE III, F. W., CUPELLO, J. M. and MEADOWS, B., (2000): Managing Six sigma: A practical Guide to Understanding, Assessing, and Implementing the Strategy that Yields Bottom-line Success; John Wiley & Sons.
[4] CHEN, Long-Fei, HSIAO, Chih-Hui and TSAI, Chin-Fa (2010): Three-stage-DEA model selections and Managerial Decision. African Journal of Business Management, 4 (14), pp. 3046-3055.
[5] KAYE, J. A. M. and FRANGOU, A., (1998): A strategic methodology to the use of advanced statistical quality improvement techniques; The TQM magazine, 10(3), pp. 169-176.
[6] MILTON, J. S. and ARNOLD, J. C., (2002). Introduction to probability and statistics: principles and applications for engineering and the computing sciences. McGraw-Hill, Inc.
[7] MONTGOMERY, D. C., (2007): Introduction to statistical quality control; John Wiley & Sons.
[8] OAKLAND, J. S., (2008): Statistical Process Control. Routledge.
[9] OTT, L. and LONGNECKER, M. (2001): An Introduction to Statistical Methods and Data Analysis; Duxbury Pacific Grove, CA.
[10] PETERS, T. J. and WATERMAN, R., (1982): In search of excellence, New York: Harper & Row, 3(1), pp. 212-217.
[11] Raheem, M. A., (2012): Statistical Quality Control. The SQC Lecture Notebook (Unpublished).
[12] SHAHIAN, D. M., WILLIAMSON, W. A., SVENSSON, L. G., RESTUCCIA, J. D. and D'AGOSTINO, R. S., (1996): Applications of statistical quality control to cardiac surgery. The Annals of Thoracic Surgery, 62(5), pp. 1351-1359.
[13] SHARMA, M. and KODALI, R., (2008): TQM implementation elements for manufacturing excellence. The TQM Journal, 20(6), pp. 599-621.
[14] SHEWHART, W. A., (1924): Some applications of statistical methods to the analysis of physical and engineering data. Bell System Technical Journal; 3(1), pp. 43-87.
[15] SMITH, G., (1998): Statistical process control and quality improvement; Prentice Hall.
[16] THOR, J., LUNDBERG, J., ASK, J., OLSSON, J., CARLI, C., HARENSTAM, K. P. and BROMMELS, M., (2007): Application of statistical process control in healthcare improvement: systematic review. Quality & safety in health care, 16(5), pp. 387-399.
[17] XIE, M. and GOH, T., (1999): Statistical Techniques for Quality; The TQM Magazine, 11(4), pp. 238-242.
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  • APA Style

    Maruf Ariyo Raheem, Aramide Titilayo Gbolahan, Itohowo Eseme Udoada. (2016). Application of Statistical Process Control in a Production Process. Science Journal of Applied Mathematics and Statistics, 4(1), 1-11. https://doi.org/10.11648/j.sjams.20160401.11

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    ACS Style

    Maruf Ariyo Raheem; Aramide Titilayo Gbolahan; Itohowo Eseme Udoada. Application of Statistical Process Control in a Production Process. Sci. J. Appl. Math. Stat. 2016, 4(1), 1-11. doi: 10.11648/j.sjams.20160401.11

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    AMA Style

    Maruf Ariyo Raheem, Aramide Titilayo Gbolahan, Itohowo Eseme Udoada. Application of Statistical Process Control in a Production Process. Sci J Appl Math Stat. 2016;4(1):1-11. doi: 10.11648/j.sjams.20160401.11

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  • @article{10.11648/j.sjams.20160401.11,
      author = {Maruf Ariyo Raheem and Aramide Titilayo Gbolahan and Itohowo Eseme Udoada},
      title = {Application of Statistical Process Control in a Production Process},
      journal = {Science Journal of Applied Mathematics and Statistics},
      volume = {4},
      number = {1},
      pages = {1-11},
      doi = {10.11648/j.sjams.20160401.11},
      url = {https://doi.org/10.11648/j.sjams.20160401.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160401.11},
      abstract = {This study evaluates the process of production of Champion Breweries Plc., located at Aka Offot, Uyo, Akwa Ibom State Nigeria. The information on the following measurable characteristics used during production were obtained; Brilliance (Haze), pH, Original Gravity (O.G) and Alcohol Percentage. Information on the number of defective crates recorded for the period of fifteen (15) days on Amstel Malta were also obtained from the bottling section. Mean (X ̅) and Range (R) control charts for variable were adopted to ascertain if the process with respect to each quality characteristics is statistically in control. The result shows that, the out-of-control points for BRILLANCE (B) were four (4) and one (1) out of twenty (20) for the mean and range charts respectively. For pH: two (2) and one (1) out of control for mean and range charts respectively. For Original Gravity (O.G): five and zero were out of control for mean and range charts respectively. For Alcohol Percentage (A): twelve and zero were out-of-control for mean and range charts respectively. Since the out-of-control points for Alcohol have exceeded the average of all points, the entire process is disregarded, and hence the process has to be overhauled. Using the P-chart to examine the defects in the finished produce daily for 15 days; it was found that 11 points were out of control, also the need for overhaul of the entire production line. Given the overall findings it could be deduced that the process was largely out-of-control, hence the need for total overhaul and the revised control schemes as appropriate. Thus, revised control schemes were formulated for the different quality characteristics for the process to be in control and the following control schemes were proposed for the future upper and lower specifications: B (X ̅: 0.6563, 0.2738; R: 0.4940, 0.00), pH (X ̅: 3.9786, 3.7916; R; 0.2871, 0.00).},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - Application of Statistical Process Control in a Production Process
    AU  - Maruf Ariyo Raheem
    AU  - Aramide Titilayo Gbolahan
    AU  - Itohowo Eseme Udoada
    Y1  - 2016/01/31
    PY  - 2016
    N1  - https://doi.org/10.11648/j.sjams.20160401.11
    DO  - 10.11648/j.sjams.20160401.11
    T2  - Science Journal of Applied Mathematics and Statistics
    JF  - Science Journal of Applied Mathematics and Statistics
    JO  - Science Journal of Applied Mathematics and Statistics
    SP  - 1
    EP  - 11
    PB  - Science Publishing Group
    SN  - 2376-9513
    UR  - https://doi.org/10.11648/j.sjams.20160401.11
    AB  - This study evaluates the process of production of Champion Breweries Plc., located at Aka Offot, Uyo, Akwa Ibom State Nigeria. The information on the following measurable characteristics used during production were obtained; Brilliance (Haze), pH, Original Gravity (O.G) and Alcohol Percentage. Information on the number of defective crates recorded for the period of fifteen (15) days on Amstel Malta were also obtained from the bottling section. Mean (X ̅) and Range (R) control charts for variable were adopted to ascertain if the process with respect to each quality characteristics is statistically in control. The result shows that, the out-of-control points for BRILLANCE (B) were four (4) and one (1) out of twenty (20) for the mean and range charts respectively. For pH: two (2) and one (1) out of control for mean and range charts respectively. For Original Gravity (O.G): five and zero were out of control for mean and range charts respectively. For Alcohol Percentage (A): twelve and zero were out-of-control for mean and range charts respectively. Since the out-of-control points for Alcohol have exceeded the average of all points, the entire process is disregarded, and hence the process has to be overhauled. Using the P-chart to examine the defects in the finished produce daily for 15 days; it was found that 11 points were out of control, also the need for overhaul of the entire production line. Given the overall findings it could be deduced that the process was largely out-of-control, hence the need for total overhaul and the revised control schemes as appropriate. Thus, revised control schemes were formulated for the different quality characteristics for the process to be in control and the following control schemes were proposed for the future upper and lower specifications: B (X ̅: 0.6563, 0.2738; R: 0.4940, 0.00), pH (X ̅: 3.9786, 3.7916; R; 0.2871, 0.00).
    VL  - 4
    IS  - 1
    ER  - 

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Author Information
  • Department of Mathematics & Statistics, University of Uyo, Uyo, Nigeria

  • Department of Computing and Information Systems, Sheffield Hallam University, Sheffield, UK

  • Department of Mathematics & Statistics, University of Uyo, Uyo, Nigeria

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