Improving Aircraft Maintenance Performance through Prescriptive Maintenance Strategies

Kurzfassung

In the past couple of years, predictive maintenance has arguably been the most discussed maintenance strategy in academia and industry. While it promises a significant operational easing and cost saving potential through the projection of system failures, it is characterized by a strong asset centricity; thus, it often only focuses on a system’s (projected) condition for issuing a maintenance task. Furthermore, the realized savings potential depends heavily on the performance of the underlying condition monitoring technologies. A recent study by (Haarman et al. 2018) among manufacturing companies from the Netherlands, Belgium, and Germany showed that many of these companies struggle in the identification of viable business case scenarios with predictive maintenance; mostly due to the limited maturity of the underlying condition monitoring technologies. Subsequently, this lack of business cases increases their hesitance to (further) invest in the development of the associated technologies, slowing the technological advancement unnecessarily. An integral part in the development of post-prognostics maintenance strategies is the identification of suitable systems to apply a prognostics-based maintenance strategy to and the determination of necessary minimum performance criteria of the underlying monitoring technology. However, the majority of research publications and industry efforts focusses on the development of condition-monitoring techniques itself and often oversimplifies this identification of business case scenarios and the subsequent integration of derived maintenance actions within the existing maintenance process environment. With these challenges in mind, we propose the next step in the evolution of post-prognostics maintenance strategies – the prescriptive maintenance approach. With this step, the scope of maintenance scheduling will be extended beyond the asset itself and incorporate the associated stakeholder’s objectives in the planning process, e.g. for the operator, a reduction in flight irregularities or, for the maintenance provider, a reduction in unjustified component removals (Wheeler et al. 2010). Thus, individual improvements (or possible drawbacks) – due to different maintenance strategies – can be attributed to the respective stakeholder. With this presentation, we will demonstrate the expected benefits for an automated tire condition monitoring system using our discrete-event simulation framework PreMaDe (Prescriptive Maintenance Developer). In particular, we are going to focus on the effects that different Prognostics and Health Management (PHM) technologies have on the operations of a short-/medium-haul aircraft fleet, the associated on-wing maintenance, and the spare parts inventory management. The presented results will provide a holistic view on the expected maintenance performance and not solely focus on monetary aspects – since real-life decision always require a trade-off between competing objectives or among multiple stakeholders. This will, subsequently, help maintenance practitioners to define suitable business case scenarios and determine necessary payments for stakeholders to be financially compensated for adversarial effects of such a prognostics-based maintenance strategy. Ultimately, this approach will enable the swift identification of systems that promise a significant optimization potential through the introduction of an adjusted maintenance strategy