FAILURE MODE AND EFFECTS ANALYSIS AND DATA MINING APPROACH TO QUALITY IMPROVEMENT IN MANUFACTURING INDUSTRY

It is important to analyze the failures and eliminate their root causes to ensure customer satisfaction and increase quality in businesses FMEA analysis is a widely used method to analyze potential or potential failures. Data mining methods can also investigate the causes of these failures. In this study, it is aimed to determine and eliminate the root causes of failures with FMEA and data mining in a machining company. FMEA and data mining have been applied to improve the quality of the business and eliminate the root causes of failures. IBM SPSS Modeler and Weka programs were used in data mining research. As a result of the research, the types of failures with a risk priority number value above 100 were reduced to an acceptable level by making improvements.C5.0 algorithm, one of the data mining classification algorithms, was applied with IBM SPSS Modeler and the factors affecting the failures of the personnel were determined. As a result of the research, it was determined that the most important reason was whether the personnel were professional or not. According to the classification result made with WEKA J48 algorithm, the most effective factor causing the personnel to make mistakes was determined as the training status of the personnel.