Concept and Economic Evaluation of Prescriptive Maintenance Strategies for an Automated Condition Monitoring System
Robert Meissner, Hendrik Meyer, Kai Wicke
Abstract
In order to reduce operating costs and increase the operational stability, the aviation industry is continuously introducing digital technologies to automate the state detection of their assets and derive maintenance decisions. Thus, many industry efforts and research activities have focused on an early state fault detection and the prediction of system failures. Since research has mainly been limited to the calculation of remaining useful lifetimes (RUL) and has neglected the impact on surrounding processes, changes on the objectives of the involved stakeholders, resulting from these technologies, have hardly been addressed in existing work. However, to comprehensibly evaluate the potential of a fault diagnosis and failure prognosis system, including its effects on adjacent maintenance processes, the condition monitoring system’s maturity level needs to be taken into account, expressed for example through the technology’s automation degree or the prognostic horizon (PH) for reliable failure projections. In this paper, we present key features of an automatic condition monitoring architecture for the example of a Tire Pressure Indication System (TPIS). Furthermore, we develop a prescriptive maintenance strategy by modeling the involved stakeholders of aircraft and line maintenance operations with their functional dependencies. Subsequently, we estimate the expected implications for a small aircraft fleet with the introduction of such a monitoring system with various levels of technological maturity. Additionally, we calculate the maintenance cost savings potential for different measurement strategies and compare these results to the current state-of-the-art maintenance approach. To estimate the effects of implementing an automated condition monitoring system, we use a discrete-event, agentbased simulation setup with an exemplary flight schedule and a simulated time span of 30 calendar days. The obtained results allow a comprehensive estimation of the maintenance related implications on airline operation and provide key aspects in the development of an airline’s prescriptive maintenance strategy.