Abstract
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 language | English |
|---|---|
| Number of pages | 13 |
| Journal | CEUR Workshop Proceedings |
| Volume | 3493 |
| Publication status | Published - 23 Sep 2023 |
| Event | PLanning And onTology wOrkshop: In conjunction with 33rd International Conference on Automated Planning and Scheduling - Prague, Czech Republic Duration: 10 Jul 2023 → 10 Jul 2023 Conference number: 33 https://icaps23.icaps-conference.org/program/workshops/plato/ |
