Abstract
As an important method that steel industries ride the Indutrie 4.0 wave, knowledge management is expected to be versatile, effective and intelligent. Mechanism modeling difficulties, numerous influencing factors and complex industrial chains hinder the development of knowledge and information integration. Using data potentials, big data analysis can be an effective way to deal with knowledge acquisition as it solves the inaccuracy and imperfection mechanism modeling may lead to. This paper proposes a big data knowledge management system(BDAKMS) adhering to data driven, intelligent analysis, service publication, dynamic update principle which can effectively extracts knowledge from mass data. Then, ontology modeling gives the knowledge unified descriptions as well as inference details combined with semantic web techniques.
Highlights
Indutrie 4.0 was put forward in Hannover Messe and brings prospects to hasten the strategic transformation of steel industries as well
Th is paper gives an ontology modeling case based on big data analytical results and achieves accurate inference through SWRL ru les and semantic web technologies
This paper focuses on discussions about ontology modeling methodology and semantic deduction
Summary
Indutrie 4.0 was put forward in Hannover Messe and brings prospects to hasten the strategic transformation of steel industries as well. Ref.[1] proposes fast matrixbased approaches to knowledge acquisition in covering informat ion systems and reduce the computational t ime compared with classical rough set, especially large-scale data sets. This method is limited to static informat ion and discretization is not universal. Steel making industries have applied big data analysis to quality management, ore blending solution optimizat ion, supply chain management, equipment fault diagnosis and financial, etc. Focusing on the difficulties in knowledge acquisition of steel industries, this paper presents a big data analysis based knowledge management structure (BDAKMS). Th is paper gives an ontology modeling case based on big data analytical results and achieves accurate inference through SWRL ru les and semantic web technologies.
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