Real-Time Maintenance Optimization Considering Health Monitoring and Additive Manufacturing



Published Nov 16, 2020
Adrian Cubillo Suresh Perinpanayagam Manuel Esperon-Miguez Philip John


Prognostics Health Management (PHM) and Integrated Vehicle Health Management (IVHM) are extensive areas of research. Whereas a lot of work has been done in diagnostics and prognostics, economic viability is an important consideration. The availability of aircraft in the aerospace sector is a critical factor. Thus, cost and downtime are the main parameters to assess the impact of IVHM. Additionally, new repair technologies, such as additive manufacturing (AM), have the potential to become standard repair procedures, complementing IVHM, and its viability also has to be assessed. However, to accurately study the impact of these factors, the characteristics of aerospace maintenance have to be taken into account. Several approaches are followed in aircraft maintenance, depending on cost, downtime and aircraft availability constraints. For instance, some parts can be repaired on the ground and assembled again on the same aircraft, while single Line Replaceable Units (LRUs) need to be removed, replaced and later repaired in the workshop without affecting the availability of the aircraft. With the gradual introduction of IVHM, the viability of any new IVHM technology needs to be assessed.
This paper describes an extensive cost and downtime model to take into account all these scenarios, including the impact of using different types of IVHM systems. The impact of IVHM and new repair technologies is discussed comparing maintenance cost and downtime of parts of LRUs and parts repaired when the aircraft is on the ground.
Secondly, a real-time maintenance case study based on IVHM, a cost and downtime model and additive manufacturing is presented. This application allows the optimization of maintenance activities by updating the available resources and their corresponding cost and time, along with the actual prediction of the Remaining Useful Life (RUL) using a health monitoring system, instead of depending on historical component/sub-system failure probabilities.

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cost-benefit analysis, AM, condition-based maintenance optimization, LRU, IVHM

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