The DLR Institute of Maintenance, Repair and Overhaul is dedicated to shaping the future of aviation through research and technology transfer. With its vision of “We Maintain Mobility for a Sustainable Future,” the institute focuses on lifecycle analysis, maintenance technologies, and the optimization of digital processes to improve technical operations in aviation. In collaboration with the DLR Institute of Propulsion Technology’s Engine Department, methods of utilizing advanced engine performance analysis with predictive maintenance methodologies are being developed to further support the advancement of data driven maintenance frameworks.
What to expect
As part of an ongoing project, methods for analysing engine degradation are being developed to determine the current condition of individual engine components. This condition data provides valuable insights into degradation behaviour and the respective remaining useful life. By incorpo rating this information, well-informed decisions can be made to optimise maintenance planning. However, a systematic approach to translating the condition of an engine, based on various per formance parameters, into triggers for maintenance measures remains a key challenge at present. Building on the completed tasks, there is an opportunity to further pursue and delve deeper into the topics within the scope of a subsequent final thesis.
Your task
- familiarization with the development of maintenance decision-making frameworks for identifying essential modelling requirements
- analyse the outputs from engine degradation models to evaluate their suitability as inputs for maintenance frameworks and identify key interfaces
- review available information on engine health indicators and degradation metrics to es tablish links with maintenance trigger criteria and thresholds
- engage with manufacturers and domain experts to enhance the understanding of current industrial practices and relevant maintenance considerations
- develop a structured methodology to relate engine health metrics to relevant maintenance events through suitable performance thresholds
- document the approach, key assumptions, and resulting threshold definitions
Your profile
- advanced studies in aerospace engineering, mechanical engineering, industrial engineer ing, or a comparable field of study
- experience in turbomachinery, data processing, analytical models and programming
- interest in aviation-specific maintenance, aircraft propulsion, lifecycle analysis, and data driven assessment methods
- strong problem-solving skills
- systematic and structured thinking
- ability to work in a team and external partners
- very good written and spoken English skills
We look forward to getting to know you!
If you have any questions about this position (Vacancy-ID 6030) please contact:
Dr. Ahmad Ali Pohya
Tel.: +49 40 2489641 143
