A digital engineering framework for information-centric modelling of drill-and-blast tunnel excavation processes

Underground drill-and-blast tunnel excavation generates large volumes of heterogeneous, phase-dependent process data. In current mining practice, this information is typically fragmented across system-specific repositories, weakly linked to excavation geometry and work phases, and difficult to reuse beyond immediate operational needs. Consequently, the primary challenge is not data availability but the lack of structured, phase-aware, and interoperable information representations that would allow excavation data to function as reusable information assets across the mining lifecycle. This paper addresses this upstream information structuring challenge by presenting an information modelling approach for drill-and-blast tunnel excavation in underground mining. The approach combines parametric Mine Information Modelling (MIM) with a structured method for identifying and formalising data dependencies between excavation phases. Central to the methodology is an open Data Use Case Matrix (DUCM©), which is used to systematically identify, prioritise, and relate excavation process data based on process dependency, temporal sensitivity, and information irreversibility. The proposed framework integrates three-dimensional parametric tunnel geometry with structured excavation process data at multiple levels of detail, including tunnel sections and individual drill holes. This enables spatially and temporally contextualised information reuse across successive excavation phases. The parametric MIM forms the foundation of an information-centric Virtual Twin (VT) that aggregates, contextualises, and visualises validated operational information through event-based updates, without relying on simulation or performance optimisation. The applicability of the approach is demonstrated through its implementation in a real underground mining context and evaluated using qualitative expert assessment focusing on applicability, internal consistency, and alignment with current mining data practices. Rather than targeting productivity optimisation, the study contributes methodological, modelling, and architectural principles for structuring drill-and-blast excavation data as reusable, geometry-linked information assets to support information-centric digital engineering in underground mining.