Design and Application of Rapid Manufacturing Domain Ontology to Support Resource Sharing

Abstract:

Facing the abundant service resources, how to make the heterogeneous distributed resources information system has the meaning that can be understand between man-machine and machines, search conveniently and implement the resources integration, achieve information access and query better as well as the interoperability between systems, it is a challenge it faces which implementing the resources sharing and intelligence services, but also a problem which to improve the service informatization level for RM industries to be solved. To facility services resource sharing in Rapid Manufacturing (RM) industry, mainly discussed demand analysis and establishment principle of RM domain ontology. Based on the many years of experience and enterprise instances, domain ontology was described conceptual and expressed knowledgeable and model structure was established. The knowledge representation method is adopted based on the domain ontology query model and partial examples of service description are given. In order to solve semantic fuzziness and realize integration, interoperability and reusability of enterprise service by building domain ontology which can satisfy shared understanding of interested parties. On this basis, integrated service system architecture was designed to support resource sharing. The methods had been applied preliminarily and would provide the basis for the future work and extended field.

• Periodical: Advanced Materials Research (Volume 670)
• Pages: 57-64
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.670.57
• Online since: March 2013
• Authors: D. Wu, Q.X. Hu, Y. Yao
• Keywords: Domain Ontology, Knowledge Representation, Resource Sharing, RM

References

[1] Z.Y. Feng, W.J. Li and X.H. Li, Ontology Engineering and Application, Tsinghua University Press, Beijing, (2007).

[2] H.K. Lin and J.A. Harding, Computers in Industry, 5 (2007) 428-437.

[3] R. Girardi and A. Leite, Knowledge-Based Systems, 21 (2008) 604-611.

[4] T.R. Gruber, International Journal of Human-Computer Studies, 5(1995) 907-928.

[5] F. Gu, editor. Research on Design of Multi-Disciplinary Ontology System, Institute of Computing Technology Chinese Academy of Sciences, Beijing, (2004).

[6] M.F. Lopez, in: Proceedings of the International Conference on AI Workshop on Ontologies and Problem-Solving Methods, (1999).

[7] G. Chen, R.Q. Lu and Z. Jin, Journal of Software, 3 (2003) 350-355.

[8] F.Q. Jiang, J.T. Li, X.L. Su, J. Ye and Z.M. Zhu, Computer Integrated Manufacturing System, 1 (2008) 1461-1465.

[9] J. Xing, Research on Method of Data Sources Selection and Constructing Domain Ontology Dalian University of Technology, Dalian, (2008).

[10] D. Wu, Q.X. Hu, Y. Yao and H.G. Zhang: Proceedings of ICMTMA2009, China, 3(2009) 730-733.

[11] K.H. Han and J.W. Park, Expert Systems with Applications 36, (2009) 744-760.

[12] T. Xuan, X.Y. Du, H. Hu and H.H. Li, Computers and Mathematics with Applications, 57 (2009) 1048-1055.

[13] D. Kucuk, Q. Salor, T. Inan, I. Çadırci and M. Ermis, Advanced Engineering Informatics, (2009).

[14] X. Jiang and A.H. Tan, Information Sciences, 179 (2009) 2794-2807.

[15] R.X. Fu, X. Yue, M. Song and Z.H. Xin, The Journal of China University of Posts and Telecommunications, 4 (2008) 126-130.

[16] D.W. Kang, J.S. Lee, S.C. Choi and K. S Kim, Expert Systems with Applications, 37 (2010) 1454-1464.