A semantic web-based framework for service composition in a cloud manufacturing environment. (January 2017)

• Record Type: Journal Article
• Authors: Lu, Yuqian; Xu, Xun
• Is Part Of: Journal of manufacturing systems. Volume 42(2017)
• Page Start: 69
• Page End: 81
• Publication Date: 2017-01
• Subjects: Cloud manufacturing -- Semantic web -- Ontology -- Expert system -- Service composition -- Knowledge management; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2016.11.004
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: Key requirements and challenges for facilitating rapid production of personalised products in cloud manufacturing. A knowledge-based service composition mechanism considering governance policies, resource access policies and etc. Implementation of the proposed service composition framework in real industrial environment. Abstract: Cloud manufacturing has been recognised as a transformative manufacturing paradigm to enable rapid production of highly customised products in a networked environment, through on-demand consumption of cloud-based manufacturing services. The fundamental issue of on-demand manufacturing service provision is service composition, where distributed manufacturing resources are mapped to personalised service requests. This paper examines knowledge-based service composition and adaptive resource planning in a cloud manufacturing environment. The intention is to develop an integrated networked environment, allowing fast resource allocation for a given service request, subject to governance policies, resource access policies, resource availability information and etcetera. The research challenge in this is to explore a feasible service composition method that facilitates easy mapping between service requests and manufacturing resources based on restrictive rule sets in the cloud and availability information about a resource. The research work in this paper analyses the relevant research challenges, proposes a practical approach and implements the solution in the form of a web-based system. The proposed system utilises distributed knowledge for intelligent service composition and adaptive resource planning. A case study is also presented to validate the performance of the proposed approach.