Akademik Veri Yönetim Sistemi
Savunma Bilimleri Dergisi, cilt.0, sa.41, ss.205-226, 2022 (Hakemli Dergi)
It is very important for businesses to keep the machines used in manufacturing in working condition by applying appropriate maintenance policies. Many studies are carried out to analyze the malfunctions that have occurred in the past and to predict the malfunctions that may occur in the future periods. Recently, data mining methods have been used frequently in the field of maintenance. In this study; maintenance and repair works, which are an important activity of an enterprise operating in the automotive sector, are discussed. It is aimed to determine the relationships between the failure and impact factors that occur in a CNC machine with a high failure rate of the enterprise and cause the production to stop very seriously. For this purpose, association rules, one of the data mining methods, were applied on the one-year failure data of the CNC machine. The application was carried out using the SPSS Modeler 18.2 program and the Apriori algorithm. By analyzing and interpreting the obtained rules, maintenance strategies that will contribute to the business economically have been put forward and the results have been interpreted.