Introduction to TIPS: a theory for creative design

A highly intriguing problem in combining artificial intelligence and engineering design is automation of the creative and innovative phases of the design process. This paper gives a brief introduction to the theory of inventive problem solving (TIPS) selected as a theoretical basis of the authors' research efforts in this field. The research is conducted in the Stevin Project of the Knowledge-Based System Group of the University of Twente (Enschede, The Netherlands) in cooperation with the Invention Machine Laboratory (Minsk, Belarus). This collaboration aims at developing a formal basis for the creation of an automated reasoning system to support creative engineering design

Knowledge based Approach for Formulating TRIZ Contradictions

AbstractThe article presents how to innovate a product using information extraction from patents literature to identify and overcome TRIZ contradictions. Each initial inventive situation has to be formulated in terms of contradictions in order to use the most effective tool for problem solving provided by the TRIZ theory.The authors propose, (1) an algorithm guiding the user to move from an indefinite problem situation to obtain a clearer problem formulation, following a process inspired to the ARIZ approach for fixing physical contradictions, and (2) some strategies and tools for selecting, acquiring and finally modeling the necessary information to improve the effectiveness in building the contradiction model.All those strategies have been implemented in a knowledge management tool called KOM, working as an automatic patent searching engine based on a functional oriented search. An exemplary application is presented to explain how KOM is integrated in the problem definition process

Innovation through pertinent patents research based on physical phenomena involved

One can find innovative solutions to complex industrial problems by looking for knowledge in patents. Traditional search using keywords in databases of patents has been widely used. Currently, different computational methods that limit human intervention have been developed. We aim to define a method to improve the search for relevant patents in order to solve industrial problems and specifically to deduce evolution opportunities. The non-automatic, semi-automatic, and automatic search methods use keywords. For a detailed keyword search, we propose as a basis the functional decomposition and the analysis of the physical phenomena involved in the achievement of the function to fulfill. The search for solutions to design a bi-phasic separator in deep offshore shows the method presented in this paper

ARIZ85 and patent-driven knowledge support

AbstractThe growing complexity of technical solutions, which encompass knowledge from different scientific fields, makes necessary, also for multi-disciplinary working teams, the consultation of information sources. Indeed, tacit knowledge is essential, but often not sufficient to achieve a proficient problem solving process. Besides, the most comprehensive tool of the TRIZ body of knowledge, i.e. ARIZ, requires, more or less explicitly, the retrieval of new knowledge in order to entirely exploit its potential to drive towards valuable solutions.A multitude of contributions from the literature support various common tasks encountered when using TRIZ and requiring additional information; most of them hold the objective of speeding up the generation of inventive solutions thanks to the capabilities of text mining techniques. Nevertheless, no global study has been conducted to fully disclose the effective knowledge requirements of ARIZ. With respect to this deficiency, the present paper illustrates an analysis of the algorithm with the specific objective of identifying the different types of information needs that can be satisfied by patents. The results of the investigation lay bare the most significant gaps of the research in the field. Further on, an initial proposal is advanced to structure the retrieval of relevant information from patent sources currently not supported by existing methodologies and software applications, so as to exploit the vast amount of technical knowledge contained in there. An illustrative experiment sheds light on the relevance of control parameters as input terms for the definition of search queries aimed at retrieving patents sharing the same physical contradiction of the problem to be treated

Case-based Reasoning for Knowledge Capitalization in Inventive Design Using Latent Semantic Analysis

International audienceNowadays, innovation represents one of the most crucial factors driving the success of companies. The Theory of Inventive Problem Solving (also known as TRIZ) is a well-established method to facilitate systematic inventive design. Although, TRIZ allows solving inventive problems through a panoply of knowledge sources, it may make inventive problem solving a time-consuming, experience demanding process and lead to waste of resources of the companies. To avoid the use of these tools and to help new users in solving their inventive problems without completely mastering TRIZ, we propose in this paper an approach based on the use of the Case-based reasoning (CBR) in order to capitalize experience. CBR is a knowledge paradigm that solves a new problem by finding the old similar cases and reusing them. The retrieval is conducted in order to find the old similar cases, and the old solutions of the retrieved cases are adapted to solve the new problem. In this paper, a systematic three-level adaptation is proposed to reduce the effort required of the users in choosing the suitable solution to solve their problem. An example is used to illustrate in detail the proposed approach

Management of «Systematic Innovation»: A kind of quest for the Holy Grail!

In this paper, authors propose a contribution for improving the open innovation processes. It shows the necessity to get an efficient methodology for open innovation in order to build a computer aided tool for inventive design in Process Systems Engineering (PSE). The proposed methodology will be evocated to be fully used in the context of the “revolutionary” concepts around the so-called factory for the future, also called integrated digital factory, innovative factory… As a result the main contribution of this paper is to propose a software prototype for an Open Computer Aided Innovation 2.0. By definition this open innovation relies on collaboration. This collaboration should enable a community, with a very broad spectrum of skills, to share data, information, knowledge and ideas. As a consequence, a first sub objective is to create a methodological framework that takes advantages of collaboration and collective intelligence (with its capacity to join intelligence and knowledge). Furthermore, the raise of the digital company and more particularly the breakthroughs in information technologies is a powerful enabler to extend and improve the potential of collective intelligence. The second sub objective is to propose a problem resolution process to impel creativity of expert but also to develop, validate and select innovative solutions. After dealing with the importance of Process Innovation and Problem solving investigation in PSE, the proposed approach originally based on an extension of the TRIZ theory (Russian acronym for Theory of Inventive Problem Solving), has been improved by using approach such as case-based reasoning, in order to tackle and revisit problems encountered in the PSE. A case study on biomass is used to illustrate the capabilities of the methodology and the tool

Encapsulating and representing the knowledge on the evaluation of an engineering system

This paper proposes a cross-disciplinary methodology for a fundamental question in product development: How can the innovation patterns during the evolution of an engineering system (ES) be encapsulated, so that it can later be mined through data mining analysis methods? Reverse engineering answers the question of which components a developed engineering system consists of, and how the components interact to make the working product. TRIZ answers the question of which problem-solving principles can be, or have been employed in developing that system, in comparison to its earlier versions, or with respect to similar systems. While these two methodologies have been very popular, to the best of our knowledge, there does not yet exist a methodology that reverseengineers and encapsulates and represents the information regarding the complete product development process in abstract terms. This paper suggests such a methodology, that consists of mathematical formalism, graph visualization, and database representation. The proposed approach is demonstrated by analyzing the design and development process for a prototype wrist-rehabilitation robot

Assessment of BioPattern in Novel Idea Generation for Bio-Inspired Design

BioPattern is a novel ideation tool for Bio-Inspired Design, built based on TRIZ, SAPPhIRE, and pattern language. It consists of an ontology, known as pattern-based ontology, and a sustainability evaluation, known as Ideal Windows. However, this framework has not been tested yet. Therefore, this article is to present the results and analysis of the case study conducted to assess this biomimicry framework. Two different groups of students, Creative & Innovation class (controlled group) and Integrated Engineering Design class (experimental group), are asked to generate innovative ideas where the experimental group employed BioPattern as the ideation tool. It is found that the level of innovation for the inventive ideas generated by the experimental group is much higher compared to that of the controlled group. Based on the inventive ideas produced by the experimental group, BioPattern is found to be efficient in ideation, able to generate effective solution, the problem-solution pairs of the ontology are adequate, and the biological solutions suggested are transferable as technological solutions. It can be concluded that BioPattern is able to bridge the biology-engineering gap