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Presenting a multi-objective intelligent dynamic model of preventive maintenance using data mining

Author

Listed:
  • Seyyed Shahram Fatemi
  • Mehrdad Javadi
  • Amir Azizi
  • Esmaeil Najafi

Abstract

The aim of this paper is the design of an intelligent dynamic model of preventive maintenance using multi-objective optimisation and data mining, based on textile and clothing industry data, especially Borujerd textile factories. Based on the samples from the semi-annual data and reports of the textile and clothing industries during the years 2013 to 2018, the data sets of the present study were compiled to perform data mining calculations. Based on the information of the comparative diagram of changing the variables of the dynamic model and by changing the initial level of the rate of change of preventive maintenance, it was determined that dynamic growth rate of the variable of 'workplace factor' with the lowest growth rate; 'technology factor' with moderate growth; 'strategy factor' with the highest growth rate; 'employee factor' with a desirable growth and 'quality factor' with a good growth rate were the results.

Suggested Citation

  • Seyyed Shahram Fatemi & Mehrdad Javadi & Amir Azizi & Esmaeil Najafi, 2023. "Presenting a multi-objective intelligent dynamic model of preventive maintenance using data mining," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 39(3), pages 362-386.
    • Handle: RePEc:ids:ijpqma:v:39:y:2023:i:3:p:362-386
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