Digital Twins for Rail Rolling Stock

Lalitphat Khongsomchit, Sakdirat Kaewunruen

Research output: Contribution to conference (unpublished)Posterpeer-review

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Abstract

This study aims to utilize AI-based digital twins for high-speed train rolling stock asset management toward the circular economy, which is a purpose of the Sustainable Development Goals (SDGs), by imagining high-speed train rolling stock component systems and using AI to create predictive maintenance models for the system.
Original languageEnglish
Publication statusPublished - 26 Jun 2024
EventClark Lecture 2024 - University of Birmingham, Birmingham, United Kingdom
Duration: 26 Jun 202426 Jun 2024
https://www.birmingham.ac.uk/schools/engineering/events/2024/clark-lecture-2024

Conference

ConferenceClark Lecture 2024
Country/TerritoryUnited Kingdom
CityBirmingham
Period26/06/2426/06/24
Internet address

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