Illkirch-Graffenstaden, France
Illkirch-Graffenstaden, France

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Yana W.,LGECO INSA Strasbourg | Zanni-Merk C.,ICUBE BFO Team | Rousselot F.,Rousselot Consultant | Cavalluccia D.,LGECO INSA Strasbourg | Collet P.,ICUBE BFO Team
International Journal of Knowledge-Based and Intelligent Engineering Systems | Year: 2013

The theory of inventive problem solving (TRIZ)was developed to solve inventive problems in different industrial fields. In recent decades, modern innovation theories and methods proposed several different knowledge sources. These knowledge sources are all built independently of the specific application and their different levels of abstraction make it quite difficult to use them without extensive knowledge about different engineering domains. Considering that all the TRIZ knowledge sources are described in short-text, the missing links among the TRIZ knowledge sources are defined based on short-text semantic similarity, which also makes it possible to ease the use of TRIZ. Meanwhile, the ontology reasoning mechanism deployed on Protégé and JESS, is used to provide heuristic solutions dynamically for TRIZ users. Firstly, TRIZ users start solving the inventive problem with the TRIZ knowledge source of their choice. Then other similar knowledge sources are obtained according to a calculation of semantic relatedness. Finally, with the help of the heuristic abstract solutions and pointers to physical-chemical-geometrical effects, specific solutions are obtained through ontology reasoning. A particular case of a "Diving Fin" is studied to show the heuristic processes of searching abstract solutions and pointers to physical-chemical-geometrical effects in detail. © 2010 - IOS Press and the authors.


Yan W.,LGECO INSA Strasbourg | Zanni-Merk C.,ICUBE BFO Team | Rousselot F.,Rousselot Consultant | Cavallucci D.,LGECO INSA Strasbourg
International Journal of Knowledge-Based and Intelligent Engineering Systems | Year: 2013

Even if TRIZ is developing increasingly both in research and education, new users always encounter difficulties in their first attempts to practice it. In such situation, Altshuller's original contradiction matrix often appears as an "easy-to-begin-with" tool. However, while not being representative of what TRIZ really is, it continues to seduce new users, teachers and trainers. This article presents an innovative method for facilitating the use of the contradiction matrix, using a semantic similarity approach and case-based reasoning. © 2013-IOS Press and the authors. All rights reserved.


Bultey A.,LGeCO | Yan W.,LGeCO | Zanni C.,ICUBE BFO Team
Procedia Engineering | Year: 2015

This paper presents a simplification of one of the TRIZ methods, the Substance-Field Analysis (SFA). Applying TRIZ methods is often time consuming and therefore a barrier to its application in the industry. Our research group strives to simplify TRIZ methods to make their use more widespread. This SFA simplification was obtained during the implementation of a computer aided SFA. This implementation implies an ontological phase, which leads to the translation of the SFA terminological and conditional knowledge in a computer language. In addition to their operational interest, the chosen computer languages (Description Logics and First Order Logic) have formal interest for the SFA. The complexity of the application of SFA has regularly been reported by the TRIZ community. The SFA terminology suffers from a lack of normalization and the 76 Standards deployment is an empirical process. We propose a clarification of the Substance-Field Modeling terminology and a systematic process for deploying the 76 Standards. Thanks to Description Logics, the SFA terminology is formalized in an automatically consistency checked model and First Order Logic ensures the systematization of the 76 Standards deployment. © 2015 The Authors. Published by Elsevier Ltd.


Zanni-Merk C.,ICube BFO Team | De Bertrand De Beuvron F.,ICube BFO Team | Rousselot F.,ICube BFO Team | Yan W.,ICube BFO Team
Applied Ontology | Year: 2013

TRIZ (the Russian acronym for Theory of Resolution of Inventive Problems) is a methodology to guide the search for inventive solutions to one, or a few, difficult problems. Classic TRIZ is not well suited to the examination of complex situations composed of many problems, sub-problems and partial solutions, strongly interconnected. It has therefore been completed to give birth, among others, to the Inventive Design Methodology (IDM) framework. TRIZ and IDM share many similarities with Artificial Intelligence methods: they both propose to solve a problem by reformulation in an abstract model. Generic solving patterns are applied to this abstract model to produce abstract solutions. The domain-specific knowledge is then used to get the final solution concept. However, neither TRIZ nor IDM's descriptions are formal enough to permit a reliable software implementation and rely mainly on the experts' manual work. Therefore this paper proposes an ontological formalization of TRIZ and IDM to overcome these difficulties and allow the development of software tools to assist TRIZ/IDM experts in their work. © 2013 - IOS Press and the authors. All rights reserved.

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