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System Dynamics Modeling and TRIZ: A Practical Approach for Inventive Problem Solving

  • Jesús Delgado-Maciel
  • Guillermo Cortes-RoblesEmail author
  • Cuauhtémoc Sánchez-Ramírez
  • Giner Alor-Hernández
  • Jorge García-Alcaraz
  • Stéphane Negny
Chapter

Abstract

The application of the theory of inventive problem solving (TRIZ) to face complex problems in the current scientific and industrial environment is an active research field. The TRIZ capacity to produce valuable technological solutions is an attractive resource to impel the innovation process and technical performance. The intensification of the research effort has unveiled new paths for proposing more efficient problem-solving tools and techniques. Among these opportunities, two are crucial in this chapter: the TRIZ limitation to observe the progression of an inventive problem in time and the difficulty that any solver faces when the system under analysis contains several interrelated problems. Nonetheless, there is an approach that analyzes a system through time and that offers some tools for modeling and simulating the different system states: system dynamics modeling. The system dynamics (SD) approach analyzes the nonlinear behavior of complex systems over time. SD is a computer-aided approach with a large extent of application domains, practically in any complex system—social, managerial, economic, or natural—defined by a set of interdependence relationships, a flow of information, and effects of causality. Hence, SD can produce useful information within a problem network and create, in combination with TRIZ, a synergy to solve inventive problems.

Keywords

Causal-loop diagram System dynamics simulation Inventive problem modeling Physical and technical contradictions 

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Notes

Acknowledgment

The National Council on Science and Technology (CONACYT), the Secretariat of Public Education (SEP) through PRODEP, and the Tecnológico Nacional de México sponsored this work. Additionally, the ROPRIN working group (Industrial Process Optimization Network) supported this work.

References

  1. Altshuller G (1984) Creativity as an exact science. CRC Press, AmsterdamGoogle Scholar
  2. Altshuller G (1999) The innovation algorithm: TRIZ, systematic innovation and technical creativity. Technical Innovation Center, Worcester, MAGoogle Scholar
  3. Ash A, Hunt L, McDonald C, Scanlan J, Bell L, Cowley R, Watson I, McIvora J, MacLeoda N et al (2015) Boosting the productivity and profitability of northern Australian beef enterprises: exploring innovation options using simulation modelling and systems analysis. Agric Syst 139:50–65. doi: 10.1016/j.agsy.2015.06.001 CrossRefGoogle Scholar
  4. Barragan J, Negny S, Cortes G, Le Lann M et al (2012) Eco-innovative design method for process engineering. Comput Chem Eng 45:137–151. doi: 10.1016/j.compchemeng.2012.06.020 CrossRefGoogle Scholar
  5. Becattini N, Borgianni Y, Cascini G, Rotini F et al (2012) Model and algorithm for computer-aided inventive problem analysis. Comput Aided Des 44(10):961–998. doi: 10.1016/j.cad.2011.02.013 CrossRefGoogle Scholar
  6. Borgianni Y, Cascini G, Rotini F et al (2015) Business process reengineering driven by customer value: a support for undertaking decisions under uncertainty conditions. Comput Ind 68:132–147. doi: 10.1016/j.compind.2015.01.001 CrossRefGoogle Scholar
  7. Chechurin S, Wits W, Bakker M et al (2015) Invention software support by integrating function and mathematical modeling. Chem Eng Res Des 103:32–39. doi: 10.1016/j.cherd.2015.07.013 CrossRefGoogle Scholar
  8. Cortes G, Negny S, Le Lann M et al (2009) Case-based reasoning and TRIZ: a coupling for innovative conception in chemical engineering. Chem Eng Process Process Intensif 48(1):239–249. doi: 10.1016/j.cep.2008.03.016 CrossRefGoogle Scholar
  9. Dawid H, Keoula Y, Kopel M, Kort M et al (2015) Product innovation incentives by an incumbent firm: a dynamic analysis. J Econ Behav Organ 117:411–438. doi: 10.1016/j.jebo.2015.07.001 CrossRefGoogle Scholar
  10. Fey V, Rivin E (2005) Innovation on demand: new product development using TRIZ. Cambridge University Press, New YorkCrossRefGoogle Scholar
  11. Forrester J (1963) Industrial dynamics. The MIT Press, Cambridge, MAGoogle Scholar
  12. Forrester J (1988) Principles of systems. Productivity Press, Portland, ORGoogle Scholar
  13. Ilevbare I, Probert D, Phaal R et al (2013) A review of TRIZ, and its benefits and challenges in practice. Technovation 33(2–3):30–37. doi: 10.1016/j.technovation.2012.11.003 CrossRefGoogle Scholar
  14. Jiang J, Sun P, Shie A et al (2011) Six cognitive gaps by using TRIZ and tools for service system design. Expert Syst Appl 38:14751–14759. doi: 10.1016/j.eswa.2011.05.005 CrossRefGoogle Scholar
  15. Kreng B, Wang J (2013) An innovation diffusion of successive generations by system dynamics – an empirical study of Nike Golf Company. Technol Forecast Soc Chang 80(1):77–87. doi: 10.1016/j.techfore.2012.08.002 CrossRefGoogle Scholar
  16. Li X, Li Q, Bai Z, Geng L et al (2009) Research on TRIZ and CAIs application problems for technology innovation. In: CAI 2009. Third IFIP WG 5.4 working conference, Harbin, China, 20–21 August 2009. Growth and development of computer-aided innovation, vol 304 of the series IFIP Advances in information and communication technology. Berlin, pp 193–202Google Scholar
  17. Lopez F, Belaud J, Negny S, LeLann J et al (2015a) Open computer aided innovation to promote innovation in process engineering. Chem Eng Res Des 103:90–107. doi: 10.1016/j.cherd.2015.08.015 CrossRefGoogle Scholar
  18. Lopez R, Belaud P, Le Lann M, Negny S et al (2015b) Using the collective intelligence for inventive problem solving: a contribution for open computer aided innovation. Expert Syst Appl 42(23):9340–9352. doi: 10.1016/j.eswa.2015.08.024 CrossRefGoogle Scholar
  19. Martins A, Pereira C, Vicente R et al (2009) An opinion dynamics model for the diffusion of innovations. Phys A Stat Mech Appl 388(15–16, 1–15):3225–3232. doi: 10.1016/j.physa.2009.04.007 CrossRefGoogle Scholar
  20. Organization for Economic Co-Operation and Development (2016) Growth in services – OECD: fostering employment, productivity and innovation. www.oecd.org. Accessed 13 Apr 2016
  21. Orloff M (2016) ABC-TRIZ: introduction to creative design thinking with modern TRIZ modeling. Springer, SwitzerlandGoogle Scholar
  22. Pokhrel C, Cruz C, Ramirez Y, Kraslawski A et al (2015) Adaptation of TRIZ contradiction matrix for solving problems in process engineering. Chem Eng Res Des 103:3–10. doi: 10.1016/j.cherd.2015.10.012 CrossRefGoogle Scholar
  23. Salamatov Y (1999) Triz: the right solution at the right time: a guide to innovative problem solving. KrasnoyarskGoogle Scholar
  24. Samara E, Georgiadis P, Bakouros I et al (2012) The impact of innovation policies on the performance of national innovation systems: a system dynamics analysis. Technovation 32(11):624–638. doi: 10.1016/j.technovation.2012.06.002 CrossRefGoogle Scholar
  25. Savransky S (2000) Engineering of creativity: introduction to TRIZ methodology of inventive problem solving. CRC Press, New YorkCrossRefGoogle Scholar
  26. Sterman J (2000) Business dynamics: systems thinking and modeling for a complex world. McGraw-Hill Education, Boston, MAGoogle Scholar
  27. The European TRIZ Association – ETRIA (2016) http://etria.eu/documents/TRIZ_academic_institutions.pdf. Accessed 29 Apr 2016
  28. Timma L, Bariss U, Blumberga A, Blumberga D et al (2015) Outlining innovation diffusion processes in households using system dynamics. Case study: energy efficiency lighting. Energy Proc 75:2859–2864. doi: 10.1016/j.egypro.2015.07.574 CrossRefGoogle Scholar
  29. Townsend M, Busenitz W (2015) Turning water into wine? Exploring the role of dynamic capabilities in early-stage capitalization processes. J Bus Ventur 30(2):292–306. doi: 10.1016/j.jbusvent.2014.07.008 CrossRefGoogle Scholar
  30. Wang C (2015) Using the theory of inventive problem solving to brainstorm innovative ideas for assessing varieties of phone-cameras. Comput Ind Eng 85:227–234. doi: 10.1016/j.cie.2015.04.003 CrossRefGoogle Scholar
  31. Wu D, Kefan X, Hua L, Shi Z, Olson D et al (2010) Modeling technological innovation risks of an entrepreneurial team using system dynamics: an agent-based perspective. Technol Forecast Soc Chang 77(6):857–869. doi: 10.1016/j.techfore.2010.01.015 CrossRefGoogle Scholar
  32. Yang J, Chen L (2012) Forecasting the design of eco-products by integrating TRIZ evolution patterns with CBR and simple LCA methods. Expert Syst Appl 39(3):2884–2892. doi: 10.1016/j.eswa.2011.08.150 CrossRefGoogle Scholar
  33. Yeo T, Pak Y, Yang Z et al (2013) Analysis of dynamic effects on seaports adopting port security policy. Transp Res Part A Policy Pract 49:285–301. doi: 10.1016/j.tra.2013.01.039 CrossRefGoogle Scholar
  34. Yoon J, Kim K (2011) An automated method for identifying TRIZ evolution trends from patents. Expert Syst Appl 38(12):15540–15548. doi: 10.1016/j.eswa.2011.06.005 CrossRefGoogle Scholar
  35. Zeng Y, Yao S (2009) Understanding design activities through computer simulation. Adv Eng Inform 23(3):294–308. doi: 10.1016/j.aei.2009.02.001 CrossRefGoogle Scholar
  36. Zhou Q, Yabar H, Mizunoya T, Higano Y et al (2016) Exploring the potential of introducing technology innovation and regulations in the energy sector in China: a regional dynamic evaluation model. J Clean Prod 112(2):1537–1548. doi: 10.1016/j.jclepro.2015.03.070 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jesús Delgado-Maciel
    • 1
  • Guillermo Cortes-Robles
    • 1
    Email author
  • Cuauhtémoc Sánchez-Ramírez
    • 1
  • Giner Alor-Hernández
    • 1
  • Jorge García-Alcaraz
    • 2
  • Stéphane Negny
    • 3
  1. 1.Instituto Tecnológico de OrizabaOrizabaMexico
  2. 2.Department of Industrial Engineering and Manufacturing—Institute of Engineering and TechnologyAutonomous University of Ciudad JuarezCiudad Juárez, ChihuahuaMexico
  3. 3.Institut National Polytechnique de Toulouse CNRS UMR 5503, PSI/Génie Industriel—INPT-ENSIACETToulouse Cedex 04France

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