A Resource Storage Model and Supply-Demand Matching Method Based on Cloud Manufacturing

Abstract

Aiming at the issue of the supply-demand matching of manufacturing resources in cloud manufacturing, an ontology-based resource storage model and resource matching algorithm are proposed. Firstly, the manufacturing information storage architecture combining relational database and non-relational database is presented to improve the query efficiency of resources. Next, according to the knowledge abstraction method of manufacturing resources, the cloud manufacturing ontology model is established, and the knowledge base is enriched by OWL and SWRL reasoning. Then, combining with the framework of cloud manufacturing resource supply-demand matching and the ontology model of manufacturing resource, the cloud resource ontology model is presented in the relational database and the non-relational database. In addition, in order to address the problem of poverty query accuracy caused by inconsistency between the customers' service requirement and the resource model in the database, resource mapping matching algorithm based on view and granularity is proposed. Finally, the above mentioned key technologies are used to establish a supply-demand service platform for cloud manufacturing resource, and combined with the processing case verification platform that the resource can be matched efficiently, accurately and automatically in cloud manufacturing.