Systems reliability and health management
Systems Reliability and Health Management is a research area dedicated to advancing the reliability, safety, and risk analysis of complex engineering systems. Find out more below.
Our research focuses on assessment methods to tackle the complexities of modern-day systems – multi-functionality, dynamic operating environments, and increasing levels of dependencies and uncertainties. These issues are exacerbated by systems now being systems-of-systems, with requirements to be highly integrated across different platforms, have seamless interoperability, where maximising performance is now a complex multi-criteria decision-making process.
With a clear focus on aviation and automotive transportation, this research supports the transition to a net zero carbon future. Priorities include enabling safety in autonomous vehicles and the connected infrastructure and maximising hybrid & electrified powertrain performance through degradation analysis and health monitoring.
The research at component level, in better understanding degradation mechanisms in new emerging technologies like batteries and fuel cells, is supported by experimental lab facilities including an environmental chamber facilitating high and low temperature operating conditions.
At system level, research in novel health monitoring methods leading to increased levels of accuracy for diagnostics and improved prognostics. For example, remaining life prediction enables improved maintenance strategies and ultimate improved system performance.
Our research focus
Our focus is to develop methods and modelling capabilities to improve inherent component reliability, maximise system operational reliability and availability, and understand & mitigate risks to make systems safer and more resilient. Our primary aims in Systems Reliability and Health Management are to:
- Develop Advanced Assessment and Analysis Methods: Innovate techniques to handle the complexities of modern systems, including multi-functionality, dynamic operating environments, and interdependencies.
- Enhance Diagnostics and Prognostics: Utilise AI and advanced data methods to improve the accuracy of system diagnostics and prognostics, ensuring better maintenance strategies and system performance.
- Maximise System Reliability and Availability: Improve component reliability and system operational availability through rigorous research and advanced modelling capabilities.
- Understand and Mitigate Risks: Identify and mitigate risks to enhance the safety and resilience of systems, particularly in critical sectors like aviation and automotive transportation.
Our research activities
Activities we address include but are not limited to:
- Component failure analysis and structure fatigue modelling
- Degradation analysis for renewable powertrains
- Enhanced Model- and data-based diagnostics
- AI methods for advanced system prognostics and remaining useful life determination
- Enhanced Predictive maintenance strategies
- Digital twins for reliability assessment
- Continuous monitoring and improvement approaches