TY - JOUR
T1 - Tackling uncertainties in aircraft maintenance routing: A review of emerging technologies
AU - Ma, Hoi Lam
AU - Sun, Yige
AU - Chung, Sai Ho
AU - Chan, Hing Kai
N1 - Funding Information:
The work described in this paper was supported by a grant from the Research Grants Council of the Hong Kong Special Administration Region, China (UGC/FDS14/E05/18).
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/8
Y1 - 2022/8
N2 - 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.
AB - 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.
KW - Air logistics
KW - Air transport
KW - Aircraft maintenance routing
KW - Emerging technologies
KW - Review paper
KW - Uncertainties
UR - http://www.scopus.com/inward/record.url?scp=85132754027&partnerID=8YFLogxK
U2 - 10.1016/j.tre.2022.102805
DO - 10.1016/j.tre.2022.102805
M3 - Journal article
AN - SCOPUS:85132754027
SN - 1366-5545
VL - 164
JO - Transportation Research Part E: Logistics and Transportation Review
JF - Transportation Research Part E: Logistics and Transportation Review
M1 - 102805
ER -