Ontology-approach for Modelling of Maintenance Capability of Complex System Environments

The increasing complexity of maintenance operations in Industry 4.0 environments demands more structured approaches to managing capability-related data across multiple stakeholders. This paper presents a proof-of-concept ontology for maintenance capability, grounded in the DOTMLPFI framework, Doctrine, Organization, Training, Materiel, Leadership, Personnel, Facilities, and Interoperability, originally developed for military capability modeling. The ontology is constructed and evaluated through a case study of the Finnish Navy's Squadron 2020 (SQ2020) Corvette Program, selected for its rich and well-defined maintenance capability requirements. By integrating model-based systems engineering principles with formal semantic technologies, and incorporating expert input, the approach enables structured reasoning over heterogeneous data relevant to maintenance planning and capability assessment. The study demonstrates how the DOTMLPFI framework, when formalized ontologically, can support improved data integration and interoperability across organizational boundaries. This supports more coherent capability development and decision-making in both military and civilian contexts. The initial ontology was validated using competency questions and logical reasoning, confirming semantic adequacy. This research contributes a reusable semantic framework for maintenance capability modeling and offers a foundation for ontology-driven decision support and future integration with digital twin architectures.