2 Citations (Scopus)


Rolling stock maintenance is essential to ensure train reliability. Adapting automation to optimise the efficiency of train maintenance procedures is crucial to maintain a smooth operation of rail transport. Information related to the scheduling and planning requirements for train maintenance procedures, however, adhere to task-specific schemas or worse, exists in unstructured formats, which hinders computerised analysis and impedes interoperability. To fill this gap, a knowledge acquisition pipeline is introduced to semantically organise textual information found in semi-structured maintenance instruction manuals. XML transformations, pattern matching and elastic search over industrial vocabularies are utilised to automatically populate a domain-specific ontology and construct a knowledge graph that describes maintenance tasks. Through demonstration, we exemplify how the resulting knowledge source can be accessed and used in Short-Term Scheduling operations.
Original languageEnglish
Number of pages13
JournalCEUR Workshop Proceedings
Publication statusPublished - 23 Sep 2023
EventPLanning And onTology wOrkshop: In conjunction with 33rd International Conference on Automated Planning and Scheduling - Prague, Czech Republic
Duration: 10 Jul 202310 Jul 2023
Conference number: 33


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