This Mini-Symposium gathered leading experts to discuss the implementation and implications of recent advances in reliability analysis and maintenance planning, with a focus on the integration of predictive maintenance, AI, digital twins, and other related topics.
Theme
There is much exciting new research on Digital Twins and AI that is making fundamental advancements in reliability and predictive maintenance. The increasing availability of condition-monitoring data has incentivized, in recent years, the development of machine learning for prognostics and diagnostics, big data analytics, and generative AI. With these, Digital Twins have also become increasingly performant.
Talk
I presented work on probabilistic health indicators for complex degradation processes, alongside contributions from academic and industrial partners.