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.
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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.
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Delgado-Maciel, J., Cortes-Robles, G., Sánchez-Ramírez, C., Alor-Hernández, G., García-Alcaraz, J., Negny, S. (2017). System Dynamics Modeling and TRIZ: A Practical Approach for Inventive Problem Solving. In: Cavallucci, D. (eds) TRIZ – The Theory of Inventive Problem Solving. Springer, Cham. https://doi.org/10.1007/978-3-319-56593-4_10
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