Interoperability in cloud manufacturing: a case study on private cloud structure for SMEs

Abstract

In recent years, cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of manufacturing paradigm. However, it also brings a new challenge which is caused by multiple cloud services and applications developed by different vendors in different platforms and programming languages. Based on the literature review, most of the cloud manufacturing research have focused on either the system or methodology level, and there are limited research works concentrating on the heterogeneous manufacturing environment and the related interoperability issues. Therefore, this research aims to tackle especially the interoperability issue in the cloud manufacturing environment. The interoperability research in computing is firstly reviewed, and the cloud manufacturing research is classified from an interoperability’s perspective. During cloud practice, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), have demands on interoperability security, and safety. Therefore, in this research, the proposed cloud manufacturing system is particularly tailored as a private cloud to achieve data and service interoperability, where the demands from SMEs are also fulfilled. The proposed system is implemented in a private manufacturing cloud structure with mobile access. The system is validated and evaluated by a case study. The quantifiable results confirm the feasibility and advantage of the proposed system, compared with the performance of conventional IT solutions.

KEYWORDS:

• Manufacturing systems
• cloud
• cloud manufacturing
• interoperability
• interoperable manufacturing

Acknowledgement

This research has received funding from EU SMARTER project, funded under the FP7 Programme (People): Marie Curie Actions, Industry-Academia Partnerships and Pathway [grant no. 610675].

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research has received funding from EU SMARTER project, funded under the FP7 Programme (People): Marie Curie Actions, Industry-Academia Partnerships and Pathway, under grant agreement no. [610675].