PLM Ontology Exploitation through Inference and Statistical Analysis: Case Study for LCC

Abstract In a time of growing complexity and amount of a product related data, ontology has show to be an efficient and convenient method for structuring and modeling the domain of interest. It provides a clear picture of all relevant concepts, their relationships and the rules they follow. It is a structured, centralized data base, that allows fast updates and prevents redundancy. Still, fast, real-time functions of today's companies impose additional requirements on a operational domain model and in this paper, we argue that product life-cycle management (PLM) ontology can meet those requirements. In that sense, tools that we propose for ontology exploitation are mainly inference on ontology rules on one side, and ontology instances extraction for the purpose of visualization and data mining on the other side. We implement these tools for the case of manufacturing company on a real life data provided and analyze benefits from the aspect of non-expert end-user. This research is done as a part of FP7 project LinkedDesign.

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