# Case Study of Expected Loss Failure Mode and Effect Analysis Model Based on Maintenance Data
## 1 Introduction
[37] suggested the expected loss model, in which failure was dependent on time, and the system was periodically monitored to prevent failures during its mission period. The loss due to each failure mode was assumed to depend on the remaining mission period of the system. Next, among some studies that have focused on improving the FMEA procedure, [PERSON] et al. proposed a systematic structure that can identify the relationship between failure modes by combining FTA and FMEA, but it has a limitation in that it consumes a lot of time. [28]. [PERSON] et al. proposed a procedural model for process FMEA based on process function and equipment model (PFEM) representing the mapping between process functions and related equipment. The process FMEA performance method using PFEM is a methodology that enables them to be found by systematically accessing failure modes, effects, and causes by using a combined voice of customer (VOC) and defect history [38]. [PERSON] et al. proposed an algorithm for assessing the risk of accidents at energy facilities, based on the FMEA, event tree analysis (ETA), and human reliability assessment (HRA) methods, will increase the level of monitoring effectiveness of repair work organization of electrical equipment and its technical condition [39]. In addition, some studies have applied FTA and ETA to FMEA to systematically identify failure modes, causes, and effects [40; 41]. Various studies are being conducted in terms of risk assessment methods and procedures to improve traditional FMEA. However, few studies suggest results applicable to the industry considering both the FMEA procedure and the risk assessment method in several previous studies, including our previous studies. Moreover, most previous studies presented risk assessment methods or procedures on an academic level, making it difficult for industrial field workers to apply the proposed methodology. Furthermore, although many studies have improved the limitations of RPNs as the risk assessment indicators, few cases have been found to present readily applicable indicators while intuitively assessing risks at industrial sites. This study proposes an expected loss-based FMEA (EL-FMEA) model to present both the FMEA procedure and risk assessment indicators. In the EL-FMEA model, maintenance record data that can be sufficiently collected in the industrial field is first defined. Furthermore, based on the maintenance record data, the calculation method of system downtime, uptime, and the failure rate is presented in detail. Then, the method of cal culating the expected loss due to the cause failure is presented. Finally, an alternative coefficient calculation method is also presented to determine whether to install a cause failure detection system based on expected loss. The composition of this study is described in detail in Section 2, defining the maintenance record data necessary for risk assessment and calculating the expected loss and the best alternative decision coefficient. In Section 3, a case study is performed based on maintenance record data processed for the experiment. Section 4 discusses the results of the case study and proposes ways to use them.