Abstract
The Korean Railroad Research Institute (KRRI) has developed the rubber tired AGT system (Model: K-AGT) between 1999 and 2005. The K-AGT is a light rail transit system does not require a driver and generally operates on an elevated railroad for transporting passengers. Accidents caused by driverless vehicles can severely affect social confidence, safety and economy therefore, it is very important to minimize the occurrences of such faults, and to accurately perform detailed maintenance tasks and thoroughly investigate the cause of any repeated failures. This research develops the web-based Preventive Maintenance (PM) system for the KAGT train system. The framework of the PM system is based on performing a reliability analysis and a failure mode effects analyses (FMEA) procedure on all the sub-systems in the K-AGT system. Out of the devices that have a low reliability, the high failure ranked devices are included high in the list for performing the overall maintenance plans. Through registration of historical failure data, the reliability indexes can be updated. Such a process is repeated continuously and can achieve very accurate predictions for device operational life times and failure rates. Therefore, this research describes the development of the overall PM system consists of a reliability analysis module, a failure mode effect analysis module, and maintenance request module.