Semantic Modeling And Visualization For Manufacturing Industry

The Internet of Things,as the key technology in the manufacturing field,can connect all kinds of equipment in factories and generates a large amount of data.Enterprise data sources are relatively independent,so information exchange is difficult.Using information for comprehensive analysis is a huge problem.Therefore,heterogeneous data integration is a challenge for most enterprises.The mainstream data integration scheme is to model and arrange the heterogeneous data by experts according to the actual situation,which is not reusable and wastes manpower greatly.Compared with traditional relational database integration,semantic modeling technology can not only relate heterogeneous data to a unified model,but also provide effective data integration for manufacturing applications.In this paper,we use a factory in Wuhan as a template.Under the existing framework of manufacturing semantic web,the semantic model of manufacturing field data is built to solve the problem of heterogeneous manufacturing data.The mapping rules for data are determined by the framework of the existing manufacturing semantic web.Since the upper framework is an abstraction of the manufacturing field,the semantic web is applicable to various manufacturing scenarios and the reusability of the model is improved.In the process of semantic modeling,the attribute column similarity measure algorithm are applied to identify similar attribute columns between tables,so that equivalence relationship between these attributes can be built.It plays an auxiliary role in improving the semantic modeling process.Because the traditional visual modeling tools cannot display the attribute information of ontology,a visualization system is designed to show the relationship between the model elements,and can browse and query data easily.Experiments show that the algorithm can filter the related attributes,which can reduce the manpower consumption and improve the modeling efficiency.Semantic model realizes the unified management of data,and its reusability is conducive to coping with the update and iteration of manufacturing production environment,laying a solid foundation for production scheduling and management.