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Performance assessment of industrial system (African Textile Manufacturers, LTD) through copula linguistic approach

Author

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  • Muhammad Idris Abubakar
  • Vijay Vir Singh

Abstract

This paper deals with the performance assessment of a textile industry, namely African Textile Manufactures (ATM) Ltd., in Chalawa, Kano industrial estate, Federal Republic of Nigeria. The entire system ATM has different sections of machines for processing various assignments. The machines in the sections have diverse capabilities. We assumed the following subsystems: spinning, weaving, pre-treatment, printing, and steaming. The failure rates of subsystems are constant, and they follow exponential distribution, while the repairs follow two types of distributions, namely general distribution and Gumbel–Hougaard family copula distribution. The system analyzed by employing supplementary variable and the Laplace transform. Various measures of reliability have been computed for differential values of failures and two types of repair. The conclusions and some recommendations are addressed to improving the management of ATM.

Suggested Citation

  • Muhammad Idris Abubakar & Vijay Vir Singh, 2019. "Performance assessment of industrial system (African Textile Manufacturers, LTD) through copula linguistic approach," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(4), pages 5-22.
    • Handle: RePEc:wut:journl:v:4:y:2019:p:5-22:id:1479
    DOI: 10.37190/ord190401
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    References listed on IDEAS

    as
    1. Monika Gahlot & V.V. Singh & Hamisu Ismial Ayagi & C.K. Goel, 2018. "Performance assessment of repairable system in series configuration under different types of failure and repair policies using copula linguistics," International Journal of Reliability and Safety, Inderscience Enterprises Ltd, vol. 12(4), pages 348-363.
    2. Qingan Qiu & Lirong Cui & Jingyuan Shen, 2018. "Availability and maintenance modeling for systems subject to dependent hard and soft failures," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 34(4), pages 513-527, July.
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