earticle

영어

This study aims to enhance the efficiency of the after-sales service (A/S) process for commercial trucks by implementing a data-driven approach. Traditional A/S methods result in long repair wait times, especially for intermittent faults requiring symptom reproduction. To address this, a system that records Diagnostic Trouble Code (DTC) and Vehicle Running Mode (VRM) data at failure moments is proposed. By storing data from 10 seconds before and after an event, fault diagnosis can be performed without symptom reproduction. Additionally, for exported vehicles, stored data enables remote analysis, overcoming real-time data limitations due to varying environmental factors. This approach improves maintenance reliability, optimizes repair accuracy, and supports proactive quality improvements for newly developed vehicles.