The biological domain has the potential to offer a rich source of analogies to solve engineering design problems. However, due to the complexity embedded in biological systems, adding to the lack of structured, detailed, and searchable knowledge bases, engineering designers find it hard to access the knowledge in the biological domain, which therefore poses challenges in understanding the biological concepts in order to apply these concepts to engineering design problems. In order to assist the engineering designers in problem-solving, we report, in this paper, a web-based tool called Idea-Inspire 4.0 that supports analogical design using two broad features. First, the tool provides access to a number of biological systems using a searchable knowledge base. Second, it explains each one of these biological systems using a multi-modal representation: that is, using function decomposition model, text, function model, image, video, and audio. In this paper, we report two experiments that test how well the multi-modal representation in Idea-Inspire 4.0 supports understanding and application of biological concepts in engineering design problems. In one experiment, we use Bloom's method to test “analysis” and “synthesis” levels of understanding of a biological system. In the next experiment, we provide an engineering design problem along with a biological-analogous system and examine the novelty and requirement-satisfaction (two major indicators of creativity) of resulting design solutions. In both the experiments, the biological system (analogue) was provided using Idea-Inspire 4.0 as well as using a conventional text-image representation so that the efficacy of Idea-Inspire 4.0 is tested using a benchmark.
It is well-known that creativity is crucial for sustaining a product against competition. Many factors have been proposed in the literature as indicators of creativity, among which outcome-characteristics-based factors are considered the most reliable; among these, the creativity of an outcome is often indicated by two major factors:noveltyandusefulness. Only a few studies address as to how creativity assessment methods and their results can be used during the design process. To systematically address the issue of how to influence creativity of design solutions, the following questions have been framed. (1) Which factors should be used as indicators of creativityconsistentlyacross different phases of the engineering design process? (2) How can creativity be assessed in terms of these factors during the engineering design process? In this work, we considernoveltyandusefulnessas the necessary factors forcreativity. It is found, however, that it is not possible todirectlyassess theusefulnessof outcomes during the design process. Therefore,requirement satisfactionis used as a proxy forusefulness. We propose a creativity assessment method that usesnoveltyandrequirement satisfactionas indicators for creativity; the method can be used for assessing not only complete products but also ideas or concepts, as they evolve through the phases of the design process. The application of the method in design is explained using a detailed example from a case study.
We propose a large scalable engineering knowledge base as an integrated knowledge graph, comprising sets of (entity, relationship, entity) triples that are real-world engineering ‘facts’ found in the patent database. We apply a set of rules based on the syntactic and lexical properties of claims in a patent document to extract entities and their associated relationships that are supposedly meaningful from an engineering design perspective. Such a knowledge base is expected to support inferencing, reasoning, recalling in various engineering design tasks. The knowledge base has a greater size and coverage in comparison with the previously used knowledge bases in the engineering design literature.
We review the scholarly contributions that utilise natural language processing (NLP) techniques to support the design process. Using a heuristic approach, we gathered 223 articles that are published in 32 journals within the period 1991–present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions and others. Upon summarising and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research.
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