A Semantic Model in the Context of Maintenance: A Predictive Maintenance Case Study

Abstract

Advanced technologies in modern industry collect massive volumes of data from a plethora of sources, such as processes, machines, components, and documents. This also applies to predictive maintenance. To provide access to these data in a standard and structured way, researchers and practitioners need to design and develop a semantic model of maintenance entities to build a reference ontology for maintenance. To date, there have been numerous studies combining the domain of predictive maintenance and ontology engineering. However, such earlier works, which focused on semantic interoperability to exchange data with standardized meanings, did not fully leverage the opportunities provided by data federation to elaborate these semantic technologies further. Therefore, in this paper, we fill this research gap by addressing interoperability in smart manufacturing and the issue of federating different data formats effectively by using semantic technologies in the context of maintenance. Furthermore, we introduce a semantic model in the form of an ontology for mapping relevant data. The proposed solution is validated and verified using an industrial implementation.