Automated Retrieval of Non-Engineering Domain Solutions to Engineering Problems

Organised by: Cranfield UniversityBiological inspiration for engineering design has occurred through a variety of techniques such as creation and use of databases, keyword searches of biological information in natural-language format, prior knowledge of biology, and chance observations of nature. This research focuses on utilizing the reconciled Functional Basis function and flow terms to identify suitable biological inspiration for function based design. The organized search provides two levels of results: (1) associated with verb function only and (2) narrowed results associated with verb-noun (function-flow). A set of heuristics has been complied to promote efficient searching using this technique. An example for creating smart flooring is also presented and discussed.Mori Seiki – The Machine Tool Compan

Modeling inspiration for innovative NPD: lessons from biomimetics

International audienceIn biomimetic design, nature - natural phenomena, systems or organisms - is used as a source of inspiration for producing new ideas or concepts. While being widely recommended this approach lacks rigorous analysis and manageable systematization that would be needed in industrial contexts. Better modeling of this process of bioinspiration is a condition for applying bioinspiration to stimulate innovation in a controlled way. This paper presents a model for bioinspiration based on the framework of the C-K design theory. This model was elaborated considering a review of the existing literature on methods for implementing biomimetic design and an analysis of selected biomimetic product development case examples. The results reveal the main roles of biological knowledge in the design process (1) indication of a "design direction", meaning an expansion on the concepts space, (2) indication of knowledge domains where no or few knowledge is available, (3) reorganization of the knowledge base, activating knowledge bases that would not otherwise be activated. This improved understanding of the bioinspiration process outlines more sophisticated and profound conditions that have to be managed for creating value

Modeling the Cellular Level of Natural Sensing with the Functional Basis for the Design of Biomimetic Sensor Technology

After surveying biology for natural sensing solutions six main types of extraneous sensing were identified across the biological kingdoms. Natural sensing happens at the cellular level with receptor cells that respond to photo, chemo, eletro, mechano, thermo and magnetoreceptor-type stimuli. At the highest level, all natural sensing systems have the same reaction sequence to stimuli: perception, transduction, and response. This research is exploring methods for knowledge transfer between the biological and engineering domains. With the use of the Functional Basis, a well-defined modeling language, the ingenuity of natural sensing can be captured through functional models and crossed over into the engineering domain, for design or inspiration. Furthermore, a morph-matrix that lists each component in the model can easily compare and contrast the biological and engineering design components, effectively bridging the two design domains. The six main types of receptor families were modeled for the Animalia and Plantae Kingdoms, from the highest to the 4th sub-level, with emphasis on the transduction sequence. To make the biological sensing models accessible to design engineers they were placed in the Missouri University of Science & Technology Design Repository as artifacts. The models can then be utilized for concept generation and biomimetic design through searching the design repository by functional characteristics. An example of a biomimetic navigation product based on the principle of electric fish is provided to illustrate the utilization of the natural sensing models, morph-matrices and design repository

Comparing novelty of designs from biological-inspiration with those from brainstorming

This research aims to understand the significance of biological-analogies in fostering novelty by comparing biological-analogies with other design methods for idea generation. Among other design methods, brainstorming was chosen here as benchmark. Four studies were conducted to compare: (i) the levels of abstraction at which concepts were ideated using biological inspiration (represented using biocards) with that using traditional brainstorming; and (ii) the novelty of concepts produced by using these two design methods. Concepts produced in these studies were evaluated for levels of abstraction at which they were ideated, average novelty, and proportion of high-novelty concepts. Results suggest that concepts generated using biocards were ideated at higher abstraction levels than those using brainstorming, but neither were at the highest abstraction levels. The average novelty of concepts produced using biocards was found to be greater than that using brainstorming; however, no statistically significant difference was found in the proportion of high-novelty concepts. We suspect the lack of biological knowledge and cultural difference among the subjects involved in our studies as the two reasons behind the results. The results demonstrate that the design methods substantially influence the novelty of concepts generated, while indicating the need for better training in effective use of biological-analogies

Towards a design process for computer-aided biomimetics

Computer-Aided Biomimetics (CAB) tools aim to support the integration of relevant biological knowledge into biomimetic problem-solving processes. Specific steps of biomimetic processes that require support include the identification, selection and abstraction of relevant biological analogies. Existing CAB tools usually aim to support these steps by describing biological systems in terms of functions, although engineering functions do not map naturally to biological functions. Consequentially, the resulting static, functional view provides an incomplete understanding of biological processes, which are dynamic, cyclic and self-organizing. This paper proposes an alternative approach that revolves around the concept of trade-offs. The aim is to include the biological context, such as environmental characteristics, that may provide information crucial to the transfer of biological information to an engineering application. The proposed design process is exemplified by an illustrative case study

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

Classification of Biological Phenomena to Aid in Search and Retrieval for Biomimicry

Biomimetic design offers an avenue for designers to expand the solution realm by offering surface dissimilar analogies. However, a significant challenge within biomimetic design has been offering a suitable method for discovery and retrieval of inspiring biological phenomena to aid in conceptual design. This research proposes an approach for classifying both biological systems and engineering products into the type of problem being addressed. This allows designers to search for inspirational phenomena based on the type of problem that they are trying to solve. Initially this classification is performed with product-phenomenon pairings that have already been attributed to biomimetic design from an online database of bio-inspired products. Three experiments are performed to develop and validate the set of classifications. These experiments tested designers\u27 ability to classify biological phenomena, evaluated the classifications, and validated the correctness of the classification for each product-phenomenon pairing. The experiments resulted in a classification schema of six problem types: materials, machines, fluids and dynamics, heat transfer, mechanics of materials, and energy. The average Kappa is 0.73, which is significant agreement between raters. The product classification was performed by three separate raters and showed a high level of inter-rater agreement. Furthermore two raters classified the products using a primary and secondary classification schema. The primary and secondary classifications resulted in a Kappa value of 0.92. Future research work to complement the classification scheme is the identification of rules based from text mining of biologically inspired products. Specifically text mining approaches and Artificial Neural Networks (ANN), as well as a biological classification are integrated to discover relations

Enhancing creativity through Biological Stimuli during new products ideation

The development of new and innovative products consists in a competitive advantage, allowing companies to overcome competitors, maintain or even increase its market share. As the product development cycle is shortening, a greater effort is required at the ideation of new technologies and products. In this context, the bio-inspired design has been receiving attention as a creativity strengthening method. However, the majority of methods and tools proposed in this field present biological stimuli in the form of literature extracts, requiring a great cognitive effort from the design teams in abstracting principles to generate ideas. In this paper a systematic approach to biological stimuli development is presented, as well as its contribution during the ideation process. An experiment was conducted on the context of a product design course. As result, it was evidenced that the biological stimulators contributed to the increase of the ideas\u27 utility and variety, favoring the innovation process

Function Based Design-by-Analogy: A Functional Vector Approach to Analogical Search

Design-by-analogy is a powerful approach to augment traditional concept generation methods by expanding the set of generated ideas using similarity relationships from solutions to analogous problems. While the concept of design-by-analogy has been known for some time, few actual 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 functional analogies from data sources has been developed to provide this capability, here based on a functional basis rather than form or conflict descriptions. Building on past research, we utilize a functional vector space model (VSM) to quantify analogous similarity of an idea's functionality. We quantitatively evaluate the functional similarity between represented design problems and, in this case, patent descriptions of products. We also develop document parsing algorithms to reduce text descriptions of the data sources down to the key functions, for use in the functional similarity analysis and functional vector space modeling. To do this, we apply Zipf's law on word count order reduction to reduce the words within the documents down to the applicable functionally critical terms, thus providing a mapping process for function based search. The reduction of a document into functional analogous words enables the matching to novel ideas that are functionally similar, which can be customized various ways. This approach thereby provides relevant sources of design-by-analogy inspiration. As a verification of the approach, two original design problem case studies illustrate the distance range of analogical solutions that can be extracted. This range extends from very near-field, literal solutions to far-field cross-domain analogies.National Science Foundation (U.S.) (Grant CMMI-0855326)National Science Foundation (U.S.) (Grant CMMI-0855510)National Science Foundation (U.S.) (Grant CMMI-0855293)SUTD-MIT International Design Centre (IDC