Maintenance and Industrial Asset Management (AM) are fundamental business processes in guaranteeing the availability of physical assets at minimum risk and cost, while balancing the interests of several stakeholders. To reach operational excellence, intra- and inter-enterprise interoperability of systems is needed to support information management and integration between several involved parties. To this end, ontology engineering is relevant since it supports interoperability at technical and semantic levels. However, ontology modelling methodologies are varied, and several best practices exist, amongst which knowledge reuse. Nevertheless, reusing extant knowledge is not completely exploited so far, causing a heterogeneous ensemble of ontologies that are not orchestrated. The present work aims at promoting the adoption of knowledge reuse for ontology modelling in maintenance and AM. Therefore, an extensive review of existing ontologies for the two targeted business processes is performed with a twofold objective: firstly, to realise a cross-industrial ontological compendium, and secondly to understand the state of art of ontology modelling in maintenance and AM. To support the adoption of knowledge reuse, this practice is framed in AMODO (Asset Management Ontology Development methOdology). Finally, a laboratory-sized showcase is provided to prove the usefulness of relying on knowledge reuse during the ontology development. The results show that the developed ontology is realised faster and is inherently aligned with established ontologies, towards enterprise systems interoperability. Consequently, maintenance and AM business processes may rely on information management and integration to pursue operational excellence.

Knowledge reuse for ontology modelling in Maintenance and Industrial Asset Management

Polenghi A.;Roda I.;Macchi M.;Pozzetti A.;
2022-01-01

Abstract

Maintenance and Industrial Asset Management (AM) are fundamental business processes in guaranteeing the availability of physical assets at minimum risk and cost, while balancing the interests of several stakeholders. To reach operational excellence, intra- and inter-enterprise interoperability of systems is needed to support information management and integration between several involved parties. To this end, ontology engineering is relevant since it supports interoperability at technical and semantic levels. However, ontology modelling methodologies are varied, and several best practices exist, amongst which knowledge reuse. Nevertheless, reusing extant knowledge is not completely exploited so far, causing a heterogeneous ensemble of ontologies that are not orchestrated. The present work aims at promoting the adoption of knowledge reuse for ontology modelling in maintenance and AM. Therefore, an extensive review of existing ontologies for the two targeted business processes is performed with a twofold objective: firstly, to realise a cross-industrial ontological compendium, and secondly to understand the state of art of ontology modelling in maintenance and AM. To support the adoption of knowledge reuse, this practice is framed in AMODO (Asset Management Ontology Development methOdology). Finally, a laboratory-sized showcase is provided to prove the usefulness of relying on knowledge reuse during the ontology development. The results show that the developed ontology is realised faster and is inherently aligned with established ontologies, towards enterprise systems interoperability. Consequently, maintenance and AM business processes may rely on information management and integration to pursue operational excellence.
2022
Asset management
Interoperability
Knowledge reuse
Maintenance
Ontology
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1193314
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