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

Authors: Seyyed Shahram Fatemi; Mehrdad Javadi; Amir Azizi; Esmaeil Najafi

Addresses: Industrial Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran ' Mechanical Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iran ' Industrial Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran ' Industrial Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran

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.

Keywords: maintenance; Vensim system dynamics environment; Clementine data mining environment; fuzzy artificial neural network.

DOI: 10.1504/IJPQM.2023.132268

International Journal of Productivity and Quality Management, 2023 Vol.39 No.3, pp.362 - 386

Received: 08 Jan 2021
Accepted: 30 May 2021
Published online: 14 Jul 2023 *

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