Designing an intelligent model of preventive maintenance and repairs in the textile and clothing industry with the help of statistical analysis (case study of Borujerd textile factories)

In this study, the identification of the most important influencing factors for intelligent preventive maintenance and repair in the textile industry in interaction with manufacturing was performed using Spss 25 software. The research data set is based on the 2000 sample data and reports from the Director General of Textile Industry under the Ministry of Industry, Mine and Trade and the factories in the textile industry of Borujerd where the project was implemented on a semiannual basis as of 2015 to 2020.  This survey is significant in that it collects information in cooperation with specialists in the maintenance industry and the textile industry (information was collected from 240 establishments of 630 textile factories nationwide). The study sample size included professors, managers, and professionals from the textile industry. A comparison of the pre-test questionnaire (functional status) and the post-test questionnaire (ideal status) and statistical analysis calculations yielded the following results. The relationships between the study variables and the most important preventive maintenance and improvement factors in interaction with production in the textile industry have been classified as follows: strategy factor with the possibility of determining 34%, technology factor 30%, work environment factor 16%, staff factor 10%, the quality factor was identified by 10%.