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14 Fig. 11. The flowchart of organization, transfer, and implementation of information models in the IPDP prototype. the IPDP must be imported into a design platform to support the product design, so it should be utilized and understood in an exact design platform. Therefore, one must consider how the design platform is to understand knowledge with neutral forms (i.e. how to achieve the knowledge downloaded from the IPDP but utilized in a user application platform). Here, an implementation flowchart on how to utilize the knowledge downloaded from the IPDP into a VCþþ 6.0 program (design platform) is stated. Fig. 11 shows the diagram of the organization, transference and implementation of knowledge. The implementation manner of information models (knowledge) is concretely expounded as follows. The information models (knowledge) as expressed based on STEP, were compiled into a data dictionary and Cþþ classes using the STEP Developer 8.0. The data dictionary is the compiled binary format of information models. Under a VCþþ situation, the information models are instanced; and the instanced information model and data dictionary is stored in the SQL server database. The instanced information models contain all information of the traditional form of knowledge such as structure size, materials and characteristic parameters. The servers are connected with the SQL database via the ASP and ODBC. Users can log into the server of the IPDP, search the knowledge and download the STEP information model of the knowledge. Once the downloaded STEP information models are processed with STEP Developer 8.0, they can be directly used in the VCþþ programs (a design platform). 7. Conclusions and future work Upon analyzing the limitations of the commercial S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15 CAD and requirements of product design on knowledge resource, a framework of the IPEP with client/server structure, which used to integrate traditional product design platform and distributive knowledge repositories, is developed. The knowledge acquisition and transference is achieved over the Internet. The knowledge is represented based on the STEP standard. And the prototype of IPDP is developed successfully. The research provides a scheme to intensify the design ability of traditional product design platform, increase the speed of knowledge acquisition, and shorten the cycle of product development. Based on the ANN and the function driven concept, a new method (FDKS) for knowledge search is put forward. Superior to rule reasoning, the ANN can solve complex mapping between input and output and the FDKS method excellently implements the non-linear mapping between function of knowledge and knowledge itself. The success of the developed prototype illustrates that the mechanism of the IPDP is right and feasible. Certainly, there are many works that need further refinement before the engineering design system runs perfectly. For instance, the knowledge in repositories of the IPDP must be further enriched. In addition, the prototype stated in this paper is only used for acquiring and utilizing knowledge remotely. The methods of representation, storage and transference of knowledge have a commonality. But the application of knowledge depends on various design platforms. Therefore, the STEP pre/post processor of the commercial CAD platform needs to be considered in next-step works.
Acknowledgments This research was partially supported by an RGC project of Hong Kong under grant No. 9350007 and National Natural Science Foundation of China under the grant No. 59990472. References [1] E.B. Magrab, Integrated Product and Process Design and Development, the Product Realization Process, CRC Press, Boca Raton, New York, 1997. [2] S. Finger, T. Tomiyama, M. Mantyla, Knowledge Intensive Computer Aided Design, Kluwer Academic Publishers, London, UK, 2000. [3] K.S. Chin, T.N. Wong, Integrated product concepts development and evaluation, International Journal of Computer Integrated Manufacturing 12 (2) (1999) 179–190. [4] W.C. Regli, Internet-enabled computer-aided design, IEEE Internet Computing 1 (1) (1997) 39–51. [5] M. Terk, Changing Priorities of Research on WWW-Based Engineering Services, Workshop Proceedings of Network-centric CAD: A Research Planning Workshop, 1996, pp. 169–185. [6] H.J. Choi, S.H. Lee, A Development of Ship-block Cutting CAD Module Connected to WWW, Proceedings of the Society of CAD/ CAM Engineers Conference, 1997, pp. 16–25. [7] T. Christiansen, What is Perl?, http://language.perl.com/info/ synopsis.html. [8] J. Owen, STEP: An Introduction, Information Geometers, London: Winchester SO22 5LB (1993). [9] P. Gu, K. Chan, Product modeling using STEP, CAD 27 (3) (1995) 163–179. [10] D. Schenck, P. Wilson, Information Modeling the EXPRESS Way, Oxford University, New York, 1994. [11] http://www.steptools.com. [12] S.Q. Zhou, Q. Fu, Y.B. Xie, Research on auto-formulating topological layer of influence diagrams in class of decision analysis, System Engineering—Theory Methodology Application 8 (2) (1999) 49–52. [13] S.Q. Zhou, Y.B. Xie, Research on machine fault diagnosis based on fuzzy neural networks, Journal of Turbine Technology 41 (4) (1999) 216–219. S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15 15 [14] J.K. Kim, Neural network-based decision class analysis for building topological-level influence diagram, International Journal of Human- Computer Studies (47) (1997) 513–530. Shouqin Zhou was born in 1973. Currently, he works in the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong. He obtained the PhD degree in April 2001, and received M.Sc. in 1997, B.A. in 1994. His current research interests include distributed knowledge information system for product design; the standard for the exchange of product model data; Internet networks techniques, supply chain management, expert system, etc. Kwai-Sang Chin is an Associate Professor in the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong. Before joining the university, Dr Chin has more than ten years of experience in the manufacturing industry. He is a Chartered Engineer in the UK and Registered Professional Engineer in Hong Kong. Dr Chin is a fellow of Hong Kong Society for Quality, senior members of American Society for Quality (ASQ), Institute of Industrial Engineers (IIE) and Society of Manufacturing Engineers (SME), USA. His current research interests are new product development strategies in the Internet Age, quality management strategies beyond ISO 9000 for Hong Kong and China, and the use of Artificial Intelligence technologies in product design. Prasad K.D.V. Yarlagadda is the Director of the Mfg. Systems Engg. Research Conc., School of Mech., Mfg., & Medical Eng., Queensland University of Technology, Australia.
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