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A Design-Oriented Process Mining Framework for Railway Operations
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AI
DOI：10.3390/info17050483.png)
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Abstract
En 中文
Railway information systems routinely register the displacement of trains across the network as sequences of station passages and segment traversals. This paper proposes a design-oriented framework that systematically transforms such train displacements into event logs to enable established process mining analyses. Here, design-oriented means that the event log is not assumed to be readily available, but is explicitly constructed from railway records through modelling choices grounded in operational semantics. The framework comprises: (i) an eventization pipeline that maps displacements to semantically precise events with explicit lifecycle and case notions; (ii) construction of a timetable-derived reference model representing planned control flow; and (iii) a structural comparison and variant analysis stage that identifies execution-level deviations from the timetable-derived reference and organizes them into recurrent behavioural patterns. The paper contributes design principles for mapping train displacements into process-mining events, a timetable-derived representation of expected control flow, and an empirical demonstration on real-world railway data showing how this framework supports operational process analysis.
Keywords:
process mining
railway operations
event log generation
eventization pipeline
variant analysis