Evaluation of Predictive Maintenance Planning using the Example of Turbine Blades

Abstract

The aim of this master thesis is to evaluate the economic and operational impact of predictive planning using the example of turbine blades of business jet engines. The economic evaluation focuses on the Lyfecycle Cashflow Environment (LYFE) developed by Deutsches Zentrum für Luft- und Raumfahrt (DLR). The discrete event simulation is used to record the economic effects of various changes during the product life cycle. Regarding the stated objective, LYFE must be extended to include the operation of business jets and adequate engine wear models. In the first step, the theoretical basics are discussed, which include the BA, engine maintenance and wear models due to environmental influences. After the information has been described, the interfaces between the three theoretical blocks are identified in chapter 3. On the one hand, this serves to create the references between the individual topics and on the other to ensure the interconnections in LYFE. Finally, the modules are to interact with each other in such a way that the operational wear of the engines is determined based on the business jet operation and the engine maintenance measures are triggered accordingly. Chapter 4 explains the verification of the individual submodules and the linked interfaces. For this purpose, the physical assumptions are validated and described using a flight profile as an example. Chapter 5 then evaluates the final use cases of preventive and predictive maintenance. In addition to answering the main question of how the two maintenance concepts compare in terms of their economic potential, the results are evaluated in a further step regarding the uncertainties in the model and operation. The aim is to identify the sensitivities in the model and the impact on the metric of interest. The final chapter concludes the work with a summary and an outlook for future research.