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Classification of the State of Manufacturing Process under Indeterminacy

Author

Listed:
  • Muhammad Aslam

    (Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Osama Hasan Arif

    (Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

In this paper, the diagnosis of the manufacturing process under the indeterminate environment is presented. The similarity measure index was used to find the probability of the in-control and the out-of-control of the process. The average run length (ARL) was also computed for various values of specified parameters. An example from the Juice Company is considered under the indeterminate environment. From this study, it is concluded that the proposed diagnosis scheme under the neutrosophic statistics is quite simple and effective for the current state of the manufacturing process under uncertainty. The use of the proposed method under the uncertainty environment in the Juice Company may eliminate the non-conforming items and alternatively increase the profit of the company.

Suggested Citation

  • Muhammad Aslam & Osama Hasan Arif, 2019. "Classification of the State of Manufacturing Process under Indeterminacy," Mathematics, MDPI, vol. 7(9), pages 1-8, September.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:9:p:870-:d:268833
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    References listed on IDEAS

    as
    1. P. Jeyadurga & S. Balamurali & M. Aslam, 2018. "Design of an attribute np control chart for process monitoring based on repetitive group sampling under truncated life tests," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(24), pages 5934-5955, December.
    2. Lee Ho, Linda & Quinino, Roberto Costa, 2013. "An attribute control chart for monitoring the variability of a process," International Journal of Production Economics, Elsevier, vol. 145(1), pages 263-267.
    Full references (including those not matched with items on IDEAS)

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