| Abstract: |
Maintenance is an essential process for guaranteeing the reliability and availability of physical assets towards sustainable performance. The way maintenance could effectively impact on operations management highly relies on available data, whose volume and variety are increasing, challenging how they are stored and processed within an organization. To tackle this issue, ontology engineering seeks for guaranteeing semantic and technical interoperability for shared underlying meaning of concepts and consistent data formats. Despite the growing adoption of ontologies for industrial maintenance, some pitfalls may be envisaged by scientific and industrial practice, specifically referring to the development of multiple non-compatible ontologies that cannot be reused. Therefore, the goal of this research work is to promote semantic interoperability in industrial-maintenance related application. This is achieved by reviewing existing ontologies, later integrated and aligned, to realise a BFO (Basic Formal Ontology)-compliant taxonomy for maintenance, including physical decomposition of systems and maintenance processes. Hence, this research attempts a first step towards a unified taxonomy that, then, is the ground on which ontologies could be built upon so to be consistent each other. In the long run, semantic-based digital twin, referred to as cognitive digital twin, may be consistently established to improve sustainable performance of production systems. |