Towards a knowledge structuring framework for decision making within industry 4.0 paradigm

Abstract

This article discusses the importance of data and knowledge structuring to allow their exploitation in emergent context of industry of the future. The complexity of integrating knowledge into decision support systems is particularly due to the heterogeneity of knowledge sources and the large volume of data to be analyzed. This problematic is challenging in the context of high-speed machining of aeronautical mechanical parts because of the high quality and safety constraints requested in this business area. To answer the above problem, this paper proposes a new semantic modeling framework covering both generic business knowledge and real time data. The application to the proposed semantic models for decision aid perspective within the SmartEmma project is also discussed.