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Function Analysis Plus and Cause-Effect Chain Analysis Plus with Applications

  • Min-Gyu Lee
Chapter

Abstract

In an inventive problem-solving project, the most important steps are often problem analysis and idea generation. Recently, two practical methods for these steps were introduced by the Korean consulting industry—Function Analysis Plus (FA+) and Cause-Effect Chain Analysis Plus (CECA+). This chapter introduces an application of these two methods in a TRIZ-based Define–Analyze–Solve–Execute (DASE) roadmap for inventive problem solving. The roadmap provides problem solvers an algorithmic roadmap with systematic methods and convenient tools for analysis and ideation. Especially, with FA+ and CECA+, the solver can identify comprehensive solving directions ‘semi-automatically’, which helps the solver to generate rich ideas along diverse solving directions. As an example, these methods are applied to a project of inventing a self-watering flowerpot.

Keywords

Function analysis Cause effect chain analysis Inventive problem solving TRIZ 

Notes

Acknowledgements

I would like to thank Professor Leonid Chechurin at Lappeenranta University of Technology, Finland, and TRIZ masters Vasily Lenyashin and Yury Danilovskiy at QM&E Innovation for their guidance and help in this exciting field of innovation.

References

  1. Gerasimov, O. M. (2010). Technology of selecting tools of innovation design based on TRIZ and VEA analysis. TRIZ master dissertion. TRIZ Summit 2010. St. Petersburg, Russia.Google Scholar
  2. Lee, M.-G. (2016). How to generate simple model solutions systematically from function analysis diagram. TRIZ future conference 2016. Wroclaw, Poland.Google Scholar
  3. Lee, M.-G. (2017). How to generate ideas systematically from function analysis of an inventive problem. TRIZ future conference 2017. Lappeenranta, Finland.Google Scholar
  4. Lee, M.-G., Chechurin, L., & Leniachine, V. (2016). Improvement of cause effect chain analysis, CECA+, for systematic cause analysis and semi-automated idea generation for inventive problems. Flexible automation and intelligent manufacturing 2016. Seoul, South Korea.Google Scholar
  5. Lee, M.-G., Danilovskiy, Y., Lenyashin, V., Kim, S., & Jung, K. (2017). Introduction to a mainstream Korean TRIZ methodology, DASE, and its application in Korea. International conference on systematic innovation 2017. Beijing, People’s Republic of China.Google Scholar
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Copyright information

© The Author(s) 2019

Authors and Affiliations

  • Min-Gyu Lee
    • 1
    • 2
  1. 1.Department of Industrial Engineering and ManagementLappeenranta University of TechnologyLappeenrantaFinland
  2. 2.QM&E Innovation & Uni Innovation LabBundang-gu, Seongnam-si, Gyeonggi-doSouth Korea

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