Application of intelligent analysis to identify defective vehicle components

Abstract

The article shows the possibility of using intelligent analysis in a vehicle service when assessing the vehicle reliability. It was hypothesized that the use of association rules in diagnostics can increase the speed of repairs and the quality of customer service, allowing to identify the nodes that are highly likely to be faulty at the same time. For this, a knowledge base was built from the patterns obtained by applying association rules to the vehicle failure statistics. An application was implemented, which, on its basis, issues recommendations to the repair worker to check certain nodes based on the already identified defective nodes entered into the program. The proposed technique, together with the developed software tool, will optimize the diagnostic processes.