Aero engine health management system architecture design using multi-criteria optimization

Authors:
Rajesh Kudikala;Andrew R. Mills;Peter J. Fleming;Graham F. Tanner;Jonathan E. Holt
Affiliations:
The University of Sheffield, Sheffield, United Kingdom;The University of Sheffield, Sheffield, United Kingdom;The University of Sheffield, Sheffield, United Kingdom;Rolls-Royce plc, Derby, United Kingdom;Rolls-Royce plc, Derby, United Kingdom
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

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Abstract

A design process for system architecture design using multi-criteria optimization is described using a case study of an aero engine health management (EHM) system. The EHM system functional operations need to be deployed in order to satisfy their operational attribute requirements within the constraints of resource limitations. Considering the large discrete search space of decision variables and many-objective functions and constraints, an evolutionary multi-objective genetic algorithm along with a progressive preference articulation (PPA) technique, is used for solving the optimization problem. Using the PPA technique, the industrial decision maker is able to identify the most significant design constraints ("hot spots") and experiment with changing goals for objectives, in order to arrive at a satisfactory non-dominated solutions that takes account of domain knowledge.