[Cite as http://purl.org/au-research/grants/arc/DE190100931]
Researchers Dr Zhixiong Li
Brief description This project aims to develop a novel data-driven dynamic reliability assessment platform to improve predictive maintenance ability in complex cyberphysical systems (CPSs). This will be achieved by identifying which degradation mechanism(s) are likely to cause an impending failure, and then highlighting the event to trigger for maintenance service or control operation. The expected outcomes are new methods and tools needed to leverage failure prognostics and prognostics-informed maintenance/control for making CPSs resilient with reduced levels of redundancy. This research will produce major advancements in extending core components’ life and durability in complex CPSs, bringing economic benefit for Australia industry.
Funding Amount $325,000
Funding Scheme Discovery Early Career Researcher Award