Investigation of factors affecting quality in an automotive main industry business with data mining

In this study, the errors that occur as a result of time-dependent changes in an automotive industry enterprise will be analyzed. The main subject of the thesis will be to examine these errors detected in the final examination and test controls, to determine the responsible ones, to analyze the results of the external factors that cause error occurrence. Data mining techniques will be used while analyzing. Studies have shown that data mining has significant benefits in quality control. Many algorithms are used in data mining techniques and it is seen that Apriori Algorithm comes to the fore in association analysis. In the thesis, the data mining technique to be used is the Apriori Algorithm, since it is aimed to determine whether the factors that affect the occurrence of errors together create the error or not. In this thesis, it is thought that the data obtained as a result of the analysis planned to be carried out in an automotive main industry enterprise will contribute to preventing the occurrence of errors and detecting the errors before the product is presented to the customer.