Tackling uncertainties in aircraft maintenance routing: A review of emerging technologies

Abstract

Aircraft maintenance routing (AMR) is crucial for both passenger airlines and cargo airlines to maintain flight operations efficiency, meanwhile it ensures that aircraft fulfill the civil aviation safety regulations in respect to maintenance checking. An optimal AMR solution can maximize the aircraft utilization for significantly increasing the airlines’ transport capacity and profitability. Therefore, extensive research works have been undertaken in this area. Traditionally, AMRs are optimized based on deterministic approaches. However, the theoretical optimality of the solution is usually difficult to achieve during practical operations due to disruptions arising from uncertainties. Thus, optimization of AMRs with uncertainty considerations has become more prevalent. More importantly, because of the maturity of technologies such as sensors nowadays, applications of these emerging technologies to tackle uncertainties have attracted much attention. Motivated by this, we conducted a critical review on AMR papers in handling uncertainties with emerging technologies. Currently, this is the first review in AMRs that contributes by systematically reviewing the emerging technologies in handling uncertainties in AMR. By reviewing 75 papers in the area, we have categorized the papers into four areas: uncertainty and robust solutions, big data and machine learning, smart technologies, and integrated information support systems. Based on the above, we also suggest some future research directions for researchers in the area.