Multi-attribute ontology-based criticality analysis of manufacturing assets for maintenance strategies planning

Planning maintenance strategies in advance with respect to the installation and running of manufacturing assets positively affects operational expenditure during their usage. However, the early stages of the asset lifecycle are poor of operational data. Thus, domain knowledge of experts, related to the asset, the process and production requirements, is the primary source to determine which maintenance strategy better fits in a specific context. Hence, ontology-based systems represent a relevant help in this direction. In this work, given the importance of the criticality analysis (CA) for maintenance planning, the CA is analyzed from an ontological perspective to automatically associate a maintenance strategy to the asset under analysis. Moreover, to unveil the power of CA, its multi-attribute nature is considered, including not only availability as guiding criterion, but also quality and energy. The developed ontology-based CA allows to (i) semantically align all involved experts, and (ii) potentiate the analysis through reasoning capabilities. Finally, preliminary results from an industrial case in a food company are shown.