Development of a Hybrid-Cloud-based Wheel-Manufacturing Service with Ontology inference for machine tools

In this paper, we design a Hybrid-cloud-based Wheel Manufacturing Service (HC-WMS), aimed at recommending cutting tools with the Ontology inference technology on hybrid cloud platforms for satisfying both the computation scalability and the data safety. On one hand, for the data safety purpose, the wheel manufacturing data are maintained in the private cloud and protected by an authority module. On the other hand, for the computation scalability purpose, the workers which are virtual machines equipped with the wheel manufacturing software are deployed in the public cloud. When a manufacturing job is issued by a user, the job request would be divided into certain manufacturing task requests which are then send to workers through the bulletin board storage. Such the bulletin board storage is designed to exchange data between the public cloud and the private cloud without knowing any cloud information for cloud manufacturing modules, and thus, the burdens of developing manufacturing system are greatly reduced in the hybrid-cloud environment. Finally, we deploy the HC-WMS to a composition of a public cloud, namely Windows Azure, and a private cloud built by using VMWare, and apply the HC-WMS to a wheel manufacturing factory for conducting integrated tests. Testing results show that the HC-WMS can successfully recommend suitable cutting tools for machining jobs, validating its competence of acting as a cloud manufacturing service.