Integración de principios inventivos de TRIZ en sistema de diseño conceptual asistido por ordenador (CAD)

Ponencia presentada en el IX Congreso Internacional de Ingeniería de Proyectos celebrado en Málaga en el año 2005The work presented proposes the integration of TRIZ inventive principles as criteria for searching design alternatives in functional reasoning CACD systems. This approach enhances the exploration of different kinds of solutions and stimulates designers’ creativity by means of a synthesis process oriented by inventive principles, thus implementing aspects concerning CAI systems in an initial divergent scheme in order to guide the designer to search for more innovative alternatives.Este trabajo propone la integración de los principios inventivos de TRIZ como criterio de búsqueda de alternativas en sistemas CACD basados en razonamiento funcional con el fin de ampliar las posibilidades de explorar distintas soluciones y de estimular la creatividad del diseñador. La aproximación presentada permite explorar distintas alternativas mediante un proceso de síntesis orientado por los principios inventivos, implementado así parte de la filosofía de los sistemas de invención asistida por ordenador (CAI) en un esquema inicial divergente, para guiar al diseñador a la búsqueda de alternativas que acerquen a la innovación

Convergence approach in experimental results

Ponencia presentada en el IX Congreso Internacional de Ingeniería de Proyectos celebrado en Málaga en el año 2005The process of synthesis is based on phases of divergence and convergence. Many authors illustrate the divergence process to find better alternatives for the design requirements. Although there are still few explanations to prevent the possible combinatorial explosion present in complex systems. The heuristic state-space approach is an estimative process that can manage the complexity in the functional reasoning process (convergence). Its use differs from that of algorithms (mathematical procedures) because it is based on commonsense general rules taken from experience. Heuristic programs are well known for their capacity for self-learning, which can generate better optimised and more efficient solutions for design requirements. This article describes a research project carried out by the Engineering Design Group of Castellón on the generation of a better solution to a real design case, through the use of the best-first search algorithm presented by Zhang. We will therefore provide another point of view on the creation of a more efficient computational framework for the automated design process.El proceso de síntesis está basado en fases de divergencia y convergencia. Diversos autores demuestran el proceso de divergencia en la forma de búsqueda para la obtención de mejores alternativas para los requerimientos de diseño. Todavía existen muy pocas manifestaciones en el proceso de convergencia para evitar las posibles explosiones combinatorias presentes en sistemas más complejos. La aproximación heurística es un proceso que puede gestionar esa complejidad en el proceso de resolución funcional (convergencia). Su uso difiere de los algoritmos (procedimientos matemáticos) por estar basada en reglas generales sacadas de las experiencias. Los programas heurísticos son conocidos por su proceso de auto-aprendizaje, lo que puede generar soluciones más optimizadas y eficientes para los requerimientos de los procesos de diseño. Este artículo expone una investigación del Grupo de Ingeniería del Diseño de Castellón en la generación de una mejor solución en un caso real de diseño, a través del uso del algoritmo de búsqueda best-first search, presentado por Zhang. Además de aportar otro punto de vista en la creación de un modelo computacional más eficiente y eficaz para el diseño automatizado

B-Cube, Behavioural modelling of technical artefacts

A new model, B-Cube, is described for managing knowledge at the behaviour level of the function–behaviour–structure framework. The model proposes a three-dimensional approach to the behavioural modelling of technical artefacts using definitions based mainly on the meta-ontology DOLCE as concepts of behaviour. The present work aims to show how these terms and those from the NIST functional basis can complement each other in functional design. It is assumed that this model achieves similar objectives with behaviours to those obtained by the NIST functional basis with functions, i.e. the representation of behaviours in CAD and KBS, a scheme for the modelling of behaviours and a universal set of behaviours. The modelling language IDEF was adapted to be able to produce a graphic example of the modelling of technical artefacts in the FBS framework using B-Cube terminology at the behaviour level

Facilitating Design-by-Analogy: Development of a Complete Functional Vocabulary and Functional Vector Approach to Analogical Search

Design-by-analogy is an effective approach to innovative concept generation, but can be elusive at times due to the fact that few methods and tools exist to assist designers in systematically seeking and identifying analogies from general data sources, databases, or repositories, such as patent databases. A new method for extracting analogies from data sources has been developed to provide this capability. Building on past research, we utilize a functional vector space model to quantify analogous similarity between a design problem and the data source of potential analogies. We quantitatively evaluate the functional similarity between represented design problems and, in this case, patent descriptions of products. We develop a complete functional vocabulary to map the patent database to applicable functionally critical terms, using document parsing algorithms to reduce text descriptions of the data sources down to the key functions, and applying Zipf’s law on word count order reduction to reduce the words within the documents. The reduction of a document (in this case a patent) into functional analogous words enables the matching to novel ideas that are functionally similar, which can be customized in various ways. This approach thereby provides relevant sources of design-by-analogy inspiration. Although our implementation of the technique focuses on functional descriptions of patents and the mapping of these functions to those of the design problem, resulting in a set of analogies, we believe that this technique is applicable to other analogy data sources as well. As a verification of the approach, an original design problem for an automated window washer illustrates the distance range of analogical solutions that can be extracted, extending from very near-field, literal solutions to far-field cross-domain analogies. Finally, a comparison with a current patent search tool is performed to draw a contrast to the status quo and evaluate the effectiveness of this work.National Science Foundation (U.S.) (grant number CMMI-0855510)National Science Foundation (U.S.) (grant number CMMI-0855326)National Science Foundation (U.S.) (grant number CMMI-0855293)SUTD-MIT International Design Centre (IDC

Design-by-analogy: experimental evaluation of a functional analogy search methodology for concept generation improvement

Design-by-analogy is a growing field of study and practice, due to its power to augment and extend traditional concept generation methods by expanding the set of generated ideas using similarity relationships from solutions to analogous problems. This paper presents the results of experimentally testing a new method for extracting functional analogies from general data sources, such as patent databases, to assist designers in systematically seeking and identifying analogies. In summary, the approach produces significantly improved results on the novelty of solutions generated and no significant change in the total quantity of solutions generated. Computationally, this design-by-analogy facilitation methodology uses a novel functional vector space representation to quantify the functional similarity between represented design problems and, in this case, patent descriptions of products. The mapping of the patents into the functional analogous words enables the generation of functionally relevant novel ideas that can be customized in various ways. Overall, this approach provides functionally relevant novel sources of design-by-analogy inspiration to designers and design teams.SUTD-MIT International Design Centre (IDC)National Science Foundation (U.S.) (Grant Numbers CMMI-0855326, CMMI-0855510, and CMMI-08552930

Generative Transformers for Design Concept Generation

Generating novel and useful concepts is essential during the early design stage to explore a large variety of design opportunities, which usually requires advanced design thinking ability and a wide range of knowledge from designers. Growing works on computer-aided tools have explored the retrieval of knowledge and heuristics from design data. However, they only provide stimuli to inspire designers from limited aspects. This study explores the recent advance of the natural language generation (NLG) technique in the artificial intelligence (AI) field to automate the early-stage design concept generation. Specifically, a novel approach utilizing the generative pre-trained transformer (GPT) is proposed to leverage the knowledge and reasoning from textual data and transform them into new concepts in understandable language. Three concept generation tasks are defined to leverage different knowledge and reasoning: domain knowledge synthesis, problem-driven synthesis, and analogy-driven synthesis. The experiments with both human and data-driven evaluation show good performance in generating novel and useful concepts.Comment: Accepted by J. Comput. Inf. Sci. En