The representation of resources plays a fundamental role for manufacturing knowledge representation and data management. However, standards and ontologies used in engineering understand resources differently, e.g., sometimes in connection to processes occurring in time at the factory's shop floor, sometimes in relation to plans which are only possibly executed. Because of this conceptual heterogeneity, misunderstandings arise concerning the basic features that characterize resources. For instance, if a resource is an entity to be used in a manufacturing process, then it must be a material entity available in the factory. Differently, when a resource is related to a plan, it is not necessarily a material thing since it may simply be a resource specification and its physical counterpart may not be even available in the factory at stake (e.g., because it still needs to be acquired). We will discuss in the presentation three approaches found in both the academic literature and engineering standards for manufacturing resource modeling. By discussing their advantages and shortcomings, we will address the need for an ontology that integrates the three perspectives within a unique modeling approach. We will report on ongoing research work based on Semantic Web languages and technologies.
Keywords: Manufacturing resource, Planning, Systems design
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