Knowledge Refinement for Engineering Knowledge Management

Abstract

Engineering design is a knowledge-intensive process, including conceptual design, detailed design, engineering analysis, assembly design, process design, and performance evaluation. Each of these tasks involves various aspects of knowledge and experience. They are the most valuable sources for capitalizing enterprise knowledge and know-how on building enterprise memory, which may become part of enterprise assets. Therefore, capturing and representing product design information, design intents, and underlining design knowledge for later reuse is the basis of and one of the key tasks in engineering knowledge management.

This study develops an approach for engineering knowledge refinement to facilitate engineering knowledge management. This approach is basically a refinement process that includes the steps of knowledge capture, knowledge representation and storage, and knowledge compilation. This study involves the development of a semantic graph for describing product-related information, design intent and know-how, a tag-based scheme for representing various types of captured product information and engineering knowledge, a case-based representation for a designed entity, and the design of a knowledge compilation model and algorithm.

The objective of this study can be achieved by performing the following tasks: (i) developing an engineering knowledge management framework, (ii) establishing an engineering knowledge refinement process, (iii) developing levels of knowledge representation schemes, and(iv) implementing engineering knowledge refinement mechanisms.

Keywords

knowledge refinement knowledge management engineering design

Get full access to this article

View all access options for this article.

References

Anderson, D.C. and Chang, T.C. (1990). Geometric Reasoning in Feature-based Design and Process Planning , Computer and Graphics, 14(2): 225–235 .

Botting, R.M. and Godwin, A.N. (1995). Analysis of the STEP Standard Data Access Interface Using Formal Methods , Computer Standard & Interfaces, 17: 437–455 .

Boyd, M.A. , Abou-Khalil, A. , Montgomery, T.A. and Gebrael, M. (1998). Development of Automated Computer-aided Diagnostic Systems Using FMECA-based Knowledge Capture Methods , In: IEEE Conference on Reliability and Maintainability Symposium.

Bylander, T. (1991). A Simple Model of Knowledge Compilation , IEEE Intelligent Systems, 6(2): 73–74 .

Chen, C. and Gelernter, H. (1991). IREF-an Interactive Theory-Driven Knowledge Refinement Tool , In: IEEE Conference on Artificial Intelligence for Application.

Chen, Y.M. and Wei, C.L. (1997). Computer-aided Feature-based Design for Net Shape Manufacturing , Computer Integrated Manufacturing System, 10(2): 147–164 .

Chen, Y.M. , Shir, W.S. and Shen, C.Y. (2002). Distributed Engineering Change Management for Allied Concurrent Engineering , International Journal of Computer Integrated Manufacturing, 15(2): 127–151 .

Chen, C.S. , Chow, J.K. , Lee, S.M. and Swift, F. (1993). Concurrent Product Design Evaluation and Decision Support , Concurrent Engineering: Methodology and Applications, 19: 235–247 .

Cho, S.J. and Lee, J.W. (2001). ADTEP: An Agent-based Decision-supporting System for Taguchi Experiment Planning , Concurrent Engineering: Research and Applications, 9(1): 2–10 .

10.

Cerezuela, C. , Cauvin, A. , Boucher, X. and Kieffer, J.P. (1998). A Decision Support System for a Concurrent Design of Cable Harnesses: Conceptual Approach and Implementation, 6(1): 43–50 .

11.

Chai, Z. , Wu, J. and Gai, G. (1993). A Model of the Knowledge Compilation , In: IEEE Region Conference on Computer, Communication, Control, and Power Engineering.

12.

Wang, C.B. , Chen, Y.M. , Chen, Y.J. and Ho, C.T. Methodology and System Framework for Knowledge Management in Allied Concurrent Engineering, to Appear.

13.

Console, L. , Terenziani, P. and Dupre, D.T. (2000). Local Reasoning and Knowledge Compilation for Efficient Temporal Abduction , IEEE Transaction on Knowledge and Data Engineering, 14(6): 1231–1248 .

14.

Craw, S. , Boswell, R. and Rowe, R. (1997). Knowledge Refinement to Debug and Maintain a Tablet Formulation System , In: IEEE International Conference on Tools with Artificial Intelligence.

15.

Danesh, M.R. and Jin, Y. (2001). An Agent-based Decision Network for Concurrent Engineering Design, 9(1): 37–46 .

16.

Ertas, A. and Jones, J.C. (1993). The Engineering Design Process, NY: Wiley .

17.

Fujita, K. and Akagi, S. (1999). Agent-based Distributed Design System Architecture for Basic Ship, 7(2): 83–89 .

18.

Honma, M. , Nakamura, H. , Nakano, A. and Tsuruta, S. (1999). Knowledge Refinement Approach Through Incorporating Case-based Knowledge in Maintenance Engineering Scheduling AI System , In: IEEE International Conference on Systems Man and Cybernetics.

19.

Huang, G.Q. and Mak, K.L. Current Aids for Engineering Change Control , Journal of Materials Processing Technology, 76(1–3): 187–191 .

20.

ISO 10313–11 (1992). Description Methods: The EXPRESS Language Reference Manual.

21.

Keller, R.M. (1991). Applying Knowledge Compilation Techniques to Model-based Reasoning , IEEE Intelligent Systems, 6(2): 82–87 .

22.

Kobayashi, S. and Nakamura, K. (1991). Knowledge Compilation and Refinement for Fault Diagnosis , IEEE Intelligent Systems, 6(5): 39–46 .

23.

Levi, K.R. , Perschbacher, D.L. , Hoffman, M.A. , Miller, C.A. , Druhan, B.B. and Shalin V.L. (1992). An Explanation-basedlearning Approach to Knowledge Compilation: a Pilot’s Associate Application , IEEE Intelligent Systems, 7(3): 45–51 .

24.

Lichti, K.A. (1993). Knowledge Capture Model for Expert Systems Development , In: International Conference on Artificial Neural Networks and Expert Systems.

25.

Liu, X. , Wang, N. and Liu, G. (1993). An Expert System Building Tool Supporting Knowledge Compilation and Management , In: International Conference on Tools with Artificial Intelligence.

26.

Mallick, S. and Krishna, S. (1999). Requirements Engineering: Problem Domain Knowledge Capture and the Deliberation Process Support , In: International Conference on Database and Expert Systems Applications.

27.

McIntosh, K.G. (1995). Engineering Data Management: A Guide to Successful Implementation, New York: McGraw-Hill Book Company .

28.

Pahl, G. , Beitz, W. and Wallace, K. (1984). Engineering Design, London: Design Council .

29.

Prasad, B. (1997). Concurrent Engineering Fundamentals Volume II: Integrated Product Development, USA: Prentice Hall .

30.

Rumbaugh, J. , Blaha, M. , Premerlani, W. , Eddy, F. and Lorensen, W. (1992). Object-oriented Modeling and Design, New Jersey: Prentice Hall .

31.

Sowa, J.F. (1984). Conceptual Structures: Information Processing in Mind and Machine, NY: IBM Systems Research Institute .

32.

Shah, J.J. and Rogers, M.T. (1988). Functional Requirements and Conceptual Design of the Feature-based Modeling System , Computer-Aided Engineering Journal, 9–15 .

33.

Tong, C. (1991). The Nature and Significance of Knowledge Compilation , IEEE Intelligent Systems, 6(2): 88–93 .

34.

Tepfenhart, W.M. , Dick, J.P. and Sowa, J.F. (1994). Conceptual Structures: Current Practices , In: International Conference on Conceptual Structures.

35.

Yamaguchi, T. and Tachibana, Y. (1991). A Technical Analysis Expert System with Knowledge Refinement Mechanism , In: International Conference on Artificial Intelligence.