Ph.D. Thesis Defense
Jamey Ackley
(Faculty Advisor: Professor Dimitri Mavris)
"An Approach to Robust Turbofan Engine Fleet Lifecycle Management"
Monday, July 27th
2:00 p.m. EDT
Collaborative Visualization Environment (CoVE) Weber SST II
Abstract
Efficient aircraft engine lifecycle management requires operators and maintenance organizations to make interconnected decisions involving maintenance planning, material management, and spare engine provisioning. These decisions directly influence lifecycle cost, fleet reliability, and consequently operational performance. However, many of these decisions are supported by independent analytical methods that do not account for their interactions or the uncertainty inherent in real-world systems. This research addresses this limitation through the development of a framework for integrated lifecycle decision support.
The proposed framework combines deterministic optimization, engine-specific material demand forecasting, system uncertainty quantification, and robust design into a unified methodology. A mathematical optimization model is first developed to generate coordinated lifecycle maintenance plans that simultaneously consider engine performance, reliability, and regulatory requirements. Subsequently, the resulting maintenance plans are used to improve material demand forecasts. The framework is then extended through stochastic simulation to quantify the effects of uncertainty on system performance metrics and to identify robust maintenance strategies.
The methodology is evaluated through a series of four controlled experiments designed to assess the significance of improvements in key performance metrics and their relative effect sizes. Results demonstrate that coordinated lifecycle optimization significantly reduces maintenance cost while maintaining operational reliability, engine-specific forecasting improves material demand prediction relative to historical methods, structured uncertainty quantification identifies the dominant drivers of lifecycle system variability, and robust design efficiently identifies lifecycle planning strategies that balance lifecycle cost, operational performance, and operational risk under uncertainty.
Collectively, this research establishes an integrated methodology for aircraft engine lifecycle management that advances both the scientific understanding of lifecycle decision-making under uncertainty and the practical application of optimization, simulation, and robust design within commercial airline maintenance operations.
Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Daniel P Schrage, School of Aerospace Engineering
Dr. Graeme J. Kennedy, School of Aerospace Engineering
Dr. Alexander Karl, Rolls-Royce
Mr. John E. Laughter, Delta Air Lines