Abstract
In order to go beyond optimization strategies in Computer Aided Innovation, it has been demonstrated that model changes are required [1,2] during Inventive Problem Solving Process (IPSP). TRIZ proposes a universal way of generating model changes thanks to contradiction statement and contradiction solving but it does not provide methods or tools for obtainting them from typical CAD or other kind of standard data. The aim of the following paper is to propose an algorithm which extracts from an object-oriented simulator a “genealogy” of contradictions systems (both physical and technical contradictions) and formulates corresponding Substance-Field models at the basis of TRIZ Inventive Standard application. This algorithm is fed by optimizations performed on various assemblages of objects constituting the simulator program. It helps disclosing contradictions that cannot be seen by domain experts due to high complexity of problem and is an additional step towards formalization and integration of TRIZ models.
Chapter PDF
Similar content being viewed by others
References
Dubois, S., Rasovska, I., De Guio, R.: Comparison of non solvable problem solving principles issued from CSP and TRIZ. In: IFIP International Federation for Information Processing. Computer-Aided Innovation, pp. 83–94. Springer, Boston (2008)
Dubois, S., Eltzer, T., De Guio, R.: A dialectical based model coherent with inventive and optimization problems. Computers in Industry 60(8), 575–583 (2009) ISSN: 0166-3615
Cavallucci, D., Eltzer, T.: Parameter network as a means for driving problem solving process. International Journal of Computer Applications in Technology 30(1-2), 125–136 (2007) ISSN: 0952-8091
Cavallucci, D., Khomenko, N.: From TRIZ to OTSM-TRIZ: addressing complexity challenges in inventive design. International Journal of Product Development 4(1-2), 4–21 (2007)
Cavallucci, D., Rousselot, F., Zanni, C.: Initial situation analysis through problem graph. CIRP Journal of Manufacturing Science and Technology 2(4), 310–317 (2010)
Eltzer, T., Lutz, P., Khomenkho, N., Cavallucci, D.: Contribution to to early stages of analysis: a framework for contradiction’s complexity representation. In: TRIZ Future, Firenze, Italy (2004)
Kucharavy, D., De Guio, R., Gautier, L., Marrony, M.: Problem Mapping for the Assessment of Technological Barriers in the Framework of Innovative Design. In: 16th International Conference on Engineering Design, ICED 2007, Ecole Centrale Paris, Paris, France (2007)
Khomenko, N., De Guio, R., Lelait, L., Kaikov, I.: A framework for OTSM-TRIZ based computer support to be used in complex problem management. International Journal of Computer Applications in Technology 30(1/2), 88–104 (2007)
Khomenko, N., De Guio, R., Cavallucci, D.: Enhancing ECN’s abilities to address inventive strategies using OTSM-TRIZ. International Journal of Collaborative Engineering 1, 98–113 (2009)
Khomenko, N., De Guio, R.: OTSM Network of Problems for representing and analysing problem situations with computer support. In: 2nd IFIP Working Conference on Computer Aided Innovation, Delphi Corporation, Technical Center Brighton, 12501 E. Grand River, Brighton, MI 48114, USA, October 8-9. Springer Publishers, Heidelberg (2007)
Cugini, U., Cascini, G., Ugolotti, M.: Enhancing interoperability in the design process – The PROSIT approach. In: Proceedings of the 2nd IFIP Working Conference on Computer Aided Innovation, Brighton, MI, USA, October 8-9. Trends in Computer-Aided Innovation, pp. 189–200. Springer, Heidelberg (2007) ISBN 9780387754550
Dubois, S., Rasovska, I., De Guio, R.: Towards an automatic extraction of Generalized System of Contradictions out of solutionless Design of Experiments. In: Growth and Development of Computer -Aided Innovation, pp. 70–79. Springer, Boston (2009)
Rasovska, I., Dubois, S., De Guio, R.: Study of different principles for automatic identification of generalized system of contradictions out of design of experiments. In: 8th International Conference of Modeling and Simulation - MOSIM 2010 - Evaluation and Optimization of Innovative Production Systems of Goods and Services, Hammamet – Tunisia, May 10-12 (2010)
Altshuller, G.: Inventive Problem Solving Algorithm: ARIZ-85C, G.S. (1956-1985), English version to be found at http://www.seecore.org/d/ariz85c_en.pdf
Conrardy, C., De Guio, R., Zuber, B.: Facetwise study of modelling activities in the algorithm for inventive problem solving ARIZ and evolutionary algorithms. In: Proceedings of the Fourth International Conference on Design Computing and Cognition. University of Stuttgart, Stuttgart (July 2010)
Koza, J.-R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge (1992) ISBN 0262111705
Koza, J.R.: Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Springer, New York (2003) ISBN: 1402074468
Goldberg, D.E.: The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Kluwer, Dordrecht (2002) ISBN 1402070985
Cascini, G., et al.: TETRIS, TEaching TRIz at School (2009), http://www.tetris-project.org/
Collet, P., et al.: EASEA platform, SONIC (Stochastic Optimisation and Nature Inspired Computing) theme of the FDBT team at Université de Strasbourg, https://lsiit.u-strasbg.fr/easea/index.php/EASEA_platform
Bultey, A., De Bertrant, De Beuvron, F., Rousselot, F.: A substance-field ontology to support the TRIZ thinking approach. International Journal of Computer Applications in Technology 30(1/2), 113–124 (2007) ISSN: 0952-8091
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 IFIP International Federation for Information Processing
About this paper
Cite this paper
Conrardy, C., de Guio, R. (2011). Automatic Extraction of a Contradiction Genealogic Tree from Optimization with an Object-Oriented Simulator. In: Cavallucci, D., de Guio, R., Cascini, G. (eds) Building Innovation Pipelines through Computer-Aided Innovation. IFIP Advances in Information and Communication Technology, vol 355. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22182-8_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-22182-8_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22181-1
Online ISBN: 978-3-642-22182-8
eBook Packages: Computer ScienceComputer Science (R0)