Hostname: page-component-848d4c4894-m9kch Total loading time: 0 Render date: 2024-04-30T14:56:33.952Z Has data issue: false hasContentIssue false
  • English
  • Français

Knowledge Management for Problem Solving Using Semistructured Contradiction Matrix Based on Physical Quantity Description

Part of: ICT for Design

Published online by Cambridge University Press:  26 July 2019

Tamotsu Murakami

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

A Contradiction Matrix of TRIZ that classifies problems to solve as contradictions of features is an effective framework of knowledge management for problem solving. The features, however, may have a problem of completeness because they may not cover contradictions about all physical phenomena. In addition, rigidly structured Contradiction Matrix may have a problem of searchability because a relevant contradiction may not be properly searched if a recorder and a retriever describe it differently. To solve these problems, this paper proposes a semistructured contradiction matrix using not TRIZ features but physical quantities in SI unit. To enable not only exact match but also partial match in searching for relevant contradictions, dimensional similarity and qualitative value similarity of physical quantity and similarity between contradictions are defined. The proposed method is implemented as software in Python and contradictions are described in XML and stored in a semistructured matrix. From the result of similarity calculation between stored contradictions, possible effectiveness of the proposed method is confirmed.

Keywords

Knowledge managementCreativityComputational design methodsTRIZQuantity dimension
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 1983 - 1992
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Ang, M.C., Ng, K.W., Ahmad, S.A. and Wahab, A.N.A. (2013), “An Engineering Design Support Tool Based on TRIZ”, Third International Visual Informatics Conference, IVIC 2013, Selangor, Malaysia, November 13-15, pp. 115–127.Google Scholar
Bhaskar, R. and Nigam, A. (1990), “Qualitative Physics Using Dimensional Analysis”, Artificial Intelligence, Vol. 45 No. 1-2, pp. 73–111. http://doi.org/10.1016/0004-3702(90)90038-2.Google Scholar
Bureau International des Poids et Mesures. (2014), SI brochure, 8th ed. (update), pp. 111–120.Google Scholar
Cavallucci, D., Rousselot, F. and Zanni, C. (2011), “An Ontology for TRIZ”, Procedia Engineering, Vol. 9, pp. 251–260. http://doi.org/10.1016/j.proeng.2011.03.116Google Scholar
Feldman, R. and Sanger, J. (2007), The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data, Cambridge University Press, New York, pp. 3–4.Google Scholar
Gruber, T.R. and Olsen, G.R. (1994), “An Ontology for Engineering Mathematics”, Fourth International Conference on Principles of Knowledge Representation and Reasoning, Bonn, Germany, pp. 1–18.Google Scholar
Hiraoka, Y., Murakami, T., Yamamoto, K., Furukawa, Y. and Sawada, H. (2016), “Method of Computer-Aided Fault Tree Analysis for High-Reliable and Safety Design”, IEEE Transactions on Reliability, Vol. 65 No. 2, pp. 687–703. http://doi.org/10.1109/TR.2015.2513050Google Scholar
Ilevbare, I.M., Probert, D. and Phaal, R. (2013), “A Review of TRIZ, and Its Benefits and Challenges in Practice”, Technovation, Vol. 33, pp. 30–37. http://doi.org/10.1016/j.technovation.2012.11.003Google Scholar
Mann, D. (2001), “An Introduction to TRIZ: The Theory of Inventive Problem Solving”, Creativity and Innovation Management, Vol. 10 No. 2, pp. 123–125.Google Scholar
Mann, D. (2002a), Hands-On Systematic Innovation, CREAX Press, Belgium (Japanese translation).Google Scholar
Mann, D. (2002b), “Assessing the Accuracy of the Contradiction Matrix for Recent Mechanical Inventions”, TRIZ Journal, pp. 1–9.Google Scholar
Mann, D. (2009), Matrix 2010: Re-updating the TRIZ Contradiction Matrix, IFR Press (Japanese translation).Google Scholar
Prickett, P. and Aparicio, I. (2012), “The development of a modified TRIZ Technical System ontology”, Computers in Industry, Vol. 63, pp. 252–264. http://doi.org/10.1016/j.compind.2012.01.006Google Scholar
Robles, G.C., Negny, S. and Lann, J.M.L. (2009), “Case-based Reasoning and TRIZ: A Coupling for Innovative Conception in Chemical Engineering”, Chemical Engineering and Processing: Process Intensification, Vol. 48 No. 1, pp. 239–249. http://doi.org/10.1016/j.cep.2008.03.016Google Scholar