The Key Technology Research of Knowledge Modeling Method for Complex Product Design

Abstract:

The purpose of this paper is to build knowledge description model for complex product design. In order to uniform the semantic of glossary in design process, an extensive glossary semantic tree is built up and the corresponding semantic similarity calculation algorithm is proposed. The complex design knowledge can be divided into instance pattern, chart pattern, formula pattern and rule pattern. The knowledge models are proposed for these four pattern knowledge models. At last, a design knowledge modeling and reusing system for complex product is achieved, and the design knowledge can be inherited by it.

• Periodical: Applied Mechanics and Materials (Volumes 52-54)
• Pages: 1193-1198
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.52-54.1193
• Online since: March 2011
• Authors: Neng Wan, Rong Mo, Zhi Yong Chang
• Keywords: Knowledge Modeling, Knowledge Reusing, Semantic Tree

References

[1] Y.S. Ong and A.J. Keane. A domain knowledge based search advisor for design problem solving environments, Engineering Applications of Artificial Intelligence. 15(1) (2002) 105-116.

DOI: 10.1016/s0952-1976(02)00016-7

[2] Shah Jahan Miah, Don Kerr et al. A generic design environment for the rural industry knowledge acquisition. Knowledge-Based Systems 21 (8) (2008) 892-899.

DOI: 10.1016/j.knosys.2008.03.054

[3] Francisco Jesus Torralba-Rodriguez et al. An incremental knowledge acquisition-based system for supporting decisions in biomedical domains. Computer Methods and Programs in Biomedicine 98 (2) 161-171.

DOI: 10.1016/j.cmpb.2009.11.006

[4] W.P. Wagner, J. Otto, Q.B. Chung. Knowledge acquisition for expert systems in accounting and financial problem domains, Knowledge-Based Systems 15 (8) (2002) 439-447.

DOI: 10.1016/s0950-7051(02)00026-6

[5] Jun Wang, Yunpeng Wu, Xuening Liu and Xiaoying Gao. Knowledge acquisition method from domain text based on theme logic model and artificial neural network, Expert System with Applications 37 (1) ( 2010) 267-275.

DOI: 10.1016/j.eswa.2009.05.009

[6] Junghwan Kim, Jaeki Song and Donald R. Jones. The cognitive selection framework for knowledge acquisition strategies in virtual communities, International Journal of Information Management (2010).

[7] F. Gomez, Building verb predicates: a computational view, in: Proceedings of the 22nd Meeting of the Association for Computational Linguistics, ACL-04, Barcelona, Spain (2004) 351–358.

DOI: 10.3115/1218955.1219001

[8] F. Gomez, Grounding the ontology on the previous termsemanticnext term interpretation algorithm, In: Proceedings of the Second International WordNet Conference, Masaryk University, Brno (2004) 124–129.

[9] F. Gomez, Carlos Segami. Semantic interpretation and knowledge extraction, Knowledge-Based Systems 20 (1) (2007) 51-60.

DOI: 10.1016/j.knosys.2006.07.002

[10] Anneli Eteläpelto. Contextual and strategic knowledge in the acquisition of design expertise. Learning and Instruction 2000; 10(2): 113-136.

DOI: 10.1016/s0959-4752(99)00014-6

[11] Gianfranco Carrara, Yehuda E. Kalay, Gabriele Novembri. Multi-modal representation of design knowledge, Automation in Construction 1 (2) (1992) 111-121.

DOI: 10.1016/0926-5805(92)90002-2

[12] Q.Z. Yang, Y. Zhang. Semantic interoperability in building design: Methods and tools, Computer-Aidied Design 38 (10) (2006) 1099-1112.

DOI: 10.1016/j.cad.2006.06.003