Modelling CECA Diagram as a State Machine
Cause-Effect Chains Analysis (CECA) is one of the main TRIZ methods used for identification of system disadvantages. The analysis results in a diagram documenting these disadvantages and causal relations between them. Although the nature of causality implies that any effect must follow its cause, the original CECA concept does not address time explicitly. This drawback has been indicated by Yoon, who proposed Occasion Axis to describe changes of system state upon meeting particular conditions specified using values of parameters. Such an axis illustrates a sequence in time and an additional requirement is to interleave nodes referring to parameters with those referring to functions, originally dubbed as Parameter-Function Pair Nexus.
The method of transforming a CECA diagram into a logical model presented during TFC 2016 conference relies on decomposing the diagram into a context-dependent layer (specific content) and a context-independent layer, representing the structure of connections. The logical model describes the structure with a set of Boolean functions, which may be minimized and analyzed in a systematic way.
This paper explores the idea of Occasion Axis and examines the possibility of converting a CECA model into a state machine with transitions between the states described by conditions referring to parameters of objects in the analyzed system or its super-system. The expected benefits of such transformation range from better understanding of the time-domain interrelations of the causes up to describing the causality using standard notation, such as UML. The paper presents rules proposed for systematic conversion of CECA diagram into state machine representation and discusses required extensions to formal state machine definition.
KeywordsCause-Effect Chains Analysis Logical model Boolean algebra State machine Harmful process
Author gratefully acknowledges Dr. Oleg Abramov for valuable materials and explanations regarding the CECA method, Mr. Piotr Salata for inspiring discussions and Mr. Dariusz Burzyński for helping to make the paper comprehensible.
- 1.Litvin, S.S., Akselrod, B.M.: Cause-Effects Chains of Undesired Effects, Methodical theses (in Russian). CPB, 1995/12/18–1996/01/03Google Scholar
- 2.Abramov, O., Kislov, A.: Cause-Effect Analysis of Engineering System’s Disadvantages, Handbook on Methodology (in Russian), Algorithm, Ltd. (2000)Google Scholar
- 3.Falkov, D.S., Misyuchenko, I.L.: Analysis of typical errors made when choosing logical functions (in Russian) (2013). http://www.metodolog.ru/node/1643. Accessed 10 July 2018
- 4.Falkov, D.S., Misyuchenko, I.L.: Characteristics of building fragments of Cause-Effect Chains with serial connection of Disadvantages (in Russian) (2013). http://www.metodolog.ru/node/1654. Accessed 10 July 2018
- 5.Efimov, A.V.: Identification of Key Disadvantages and Key Problems using Cause-Effect Chains of Undesired Effects (in Russian) (2011). http://www.metodolog.ru/node/993. Accessed 10 July 2018
- 6.Pinyayev, A.M.: A Method for Inventive Problem Analysis and Solution Based On Why-Why Analysis and Functional Clues. TRIZ Master thesis (2007)Google Scholar
- 7.Medvedev, A.V.: Algorithm for Automated Building of Cause-Effect Chains of Disadvantages (in Russian). TRIZ Master thesis (2013)Google Scholar
- 8.Souchkov, V.V.: A Guide to Root Conflict Analysis (RCA+). ICG Training & Consulting. http://www.xtriz.com/publications/RCA_Plus_July2011.pdf. Accessed 10 July 2018
- 9.Yoon, H.: Occasion axis and parameter-function pair nexus for effective building of cause effect chains. In: Souchkov, V., Kässi, T. (eds.) Proceedings of the TRIZfest-2014 International Conference, Prague, Czech Republic, pp. 184–194. MATRIZ (2014)Google Scholar
- 10.Lok, A.: A simple way to perform CECA and generate ideas in practice. In: Souchkov, V. (ed.) Proceedings of the TRIZfest-2017 International Conference, Krakow, Poland, pp. 23–30. MATRIZ (2017)Google Scholar
- 11.Chrząszcz, J., Salata, P.: Cause-effect chains analysis using boolean algebra. TRIZ Future 2016 Conference, Wroclaw, Poland (2016). In: Koziołek, S., Chechurin, L., Collan, M. (eds.) Advances and Impacts of the Theory of Inventive Problem Solving. The TRIZ Methodology, Tools and Case Studies. Springer (2018). https://doi.org/10.1007/978-3-319-96532-1
- 12.Chrząszcz, J.: Quantitative approach to cause-effect chains analysis. In: Souchkov, V. (ed.) Proceedings of the TRIZfest-2017 International Conference, Krakow, Poland, pp. 341–352. MATRIZ (2017)Google Scholar
- 13.Ikovenko, S.: Level 1 Certification TRIZ Workshop, pp. 171–193. MATRIZ (2016)Google Scholar
- 16.Lenyashin, V., Kim, H.J.: “Harmful System” – using this concept in modern TRIZ (in Russian) (2006). http://www.metodolog.ru/00859/00859.html. Accessed 10 July 2018
- 17.Axelrod, B.: Systems approach: modeling engineering systems using interactions causality scheme. In: Grundlach, K. (ed.) Proceedings of TRIZ Future 2007 Conference, Frankfurt, Germany, pp. 131–138 (2007)Google Scholar
- 18.Chrząszcz, J.: Indicating system vulnerabilities within CECA model. In: Mayer, O. (ed.) Proceedings of the TRIZfest-2018 International Conference, Lisbon, Portugal, pp. 31–37. MATRIZ (2018)Google Scholar