This thesis proposes a facility management system for providing information on failure of parts in order to improve maintenance of facilities. The proposed system is composed of three modules. The first module is called the failure-estimating module, which is implemented in SQL, samples failure data daily, and updates the failure probability of parts for given the failure data. The module can estimate failure modes or failure causes depending on whether or not a specific failure mode is detected. In case that the failure mode is detected, failure parts can be found out by utilizing RPN (Risk Priority Number) of the FMECA (Failure Modes Effects and Criticality Analysis). Otherwise, The failure mode is inferred from the failure probability using the FTA (Fault Tree Analysis). The second module is called the Android-based facility management App module, a hybrid app, which is implemented using PhoneGap in order to control camera devices. The third module is called the HTML5-based facilities management Web module, which is connected from browsers of several platforms like desktops and mobile devices. The proposed system should be effective for proactive maintenance of facilities in that it can predict the failure diagnosis and seriousness through the analysis of relevant failure modes and causes based on the failure data.