Session: DAC-05-01-Decision Making in Engineering Design

Paper Number: 90686

90686 - Aircraft Maintenance Schedule Design Optimization During a Pandemic 

The aim of this paper is to formulate and solve the aircraft maintenance scheduling design optimization problem while considering the effects of a pandemic, such as the COVID-19 pandemic. Aircraft maintenance is dependent on how much the aircraft is in service, among other factors. It is no surprise that the pandemic has significantly impacted airline operations, due to travel restrictions and people’s hesitancy to travel. Thus, it is important for airliners to consider the progression of the pandemic when designing their flight and maintenance schedules. The approach proposed in this paper addresses this issue by integrating several models. The first one is a time series forecasting model to predict future COVID-19 cases – in this paper we use a Long Short-Term Memory (LSTM) network. The second model is a simple neural network for predicting flight frequencies based on historical flight data and the results of the first model. The predicted flight frequencies are used to generate a flight schedule, which serves as input to the third model – the maintenance schedule design optimization model, which is formulated as a binary-integer programming problem. The final output from the integrated model is the optimized maintenance schedule and associated costs. To demonstrate the proposed approach, we present two examples in application to a small aircraft fleet. One is for illustrative purposes, with 3 aircraft, the other considers a fleet of 10 aircraft.

Presenting Author: Elizabeth Jordan University of Maryland

Presenting Author Biography: Elizabeth Jordan received the B.S. degree (Hons.) in mechanical engineering from the University of Maryland (UMD), College Park, MD, USA, in December 2020, where she is currently pursuing the Ph.D. degree in mechanical engineering. Her engineering work experience includes six internships and co-ops with GE Aviation and AEDC Wind Tunnel 9. She is currently a Graduate Research Assistant. Her research interests include optimization, modeling, and decision support systems and their applications in the design and operation of engineering and healthcare systems. Ms. Jordan has received several honors and awards, including the President’s Scholarship, the Dean’s List Award for five semesters, and the University Honors Citation, while at UMD. Most recently, she was awarded the Clark Doctoral Fellowship, which is one of the most prestigious fellowships for graduate engineering students at UMD.

Authors:

Elizabeth Jordan University of Maryland
Shapour Azarm University of Maryland, College Park