Chrome Angel Solutions recently presented at the Rail Delivery Group’s (RDG) annual REGS (Railway Engineering Graduate Scheme) conference for its developing Engineering community, an event aimed at giving railway graduates insight into future technologies shaping the industry.
The session, delivered jointly by Anisa Iltaf (CAS) and Steven Armstrong, Fleet Technical Manager (Grand Central), was titled “Human + Machine = Smarter Together: A Case Study in Applying AI to Predict Engine Health.” The presentation focused on recent feasibility and proof of concept projects exploring how artificial intelligence can support better engineering decisions when combined with human expertise, and presented case studies testing real world application.
The case study projects have been funded by Innovate UK and BridgeAI, and have been delivered by Chrome Angel Solutions and Amygda in collaboration with Angel Trains and Grand Central. They demonstrated the feasibility of applying machine learning–powered analytics applied to Grand Central’s engine condition data, alongside training tools being developed and tested to build AI skills and competencies within the railway workforce. Steven Armstrong highlighted how AI-based anomaly detection can identify defects without prior knowledge of the root cause, and how these insights could feed into a continuous learning cycle to support future anomaly detection. The projects are now continuing to explore the significant challenges of practically applying ML and AI in fleet engineering and delivering the clear potential benefits.
Find out more about the event in RDG’s LinkedIn post.