Affiliation:
1. Yancheng Institute of Technology
Abstract
The efficiency of design has significant impact on the overall lead time for the new product of heavy industry machinery. Case-based reasoning (CBR) can be used to heavy industry machinery design for improving the effectiveness of design. However, CBR is short of flexibility to cope with the semantic retrieval, which is the main cause of the decline in the efficiency and accuracy. Confronted with the problem, the approach has been developed based on the combining ontology and retrieval in case-based reasoning for heavy industry machinery design. Through incorporating ontology with CBR, the paper provides a flexible and comprehensive operation. An example case study of rotary drilling rig demonstrates the potential which the proposed method is more effective to retrieve cases on the semantic level.
Publisher
Trans Tech Publications, Ltd.
Reference12 articles.
1. H.E. Tseng, C.C. Chang and S.H. Chang: Expert Systems with Applications, Vol. 29 (2005) No. 4, pp.913-925.
2. M.G. Brown: Lecture Notes in Computer Science, Vol. 837 (1994), pp.132-143.
3. A. Aamodt: Lecture Notes in Computer Science, Vol. 837 (1994), pp.274-288.
4. T.R. Gruber: Knowledge Acquisition, Vol. 5 (1993) No. 2, pp.199-220.
5. Z.G. Fang, X.X. Guo, L. Xu, et al: Advances in Mechanical Engineering, vol. 2013 (2013) Article ID 943528.