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© 2016 Elsevier Ltd With a two-decade consistent research interest for Systematic Biologically-Inspired Design, a number of methods and tools to support bio-ideation have been proposed. However, objective quantification of the effects these aids have on the design outcomes is rare. This contribution presents an impact analysis of the most popular knowledge-based tool, AskNature, in the form of an outcome-based study. The results consistently support a common claim used in favour of bio-inspired design, i.e. the expectation of identifying more out-of-the-box solutions. Furthermore, to further facilitate biological solution analysis and cross-domain knowledge transfer, an adaptation to AskNature's stimuli format — i.e. adding a graphical illustration of the biological solution principle — is validated to further boost novelty. ispartof: Design Studies vol:46 pages:152-173 status: published

Manufacturers strive to rapidly develop novel products and offer solutions that meet the emerging customer needs. The Lead User Method, emerging from studies on sources of innovation by the scientific community, offers a validated approach to identify users with innovation ideas to support rapid and successful new product development process. The approach has been more recently applied on online communities, where collection and analysis of rich user data are performed by expert practitioners. In this paper, feature extraction techniques are outlined, that enable automated classification and identification of lead users that are present in online communities. The authors describe two case studies to construct a classification model that is then used to identify online lead users for confectionery products, and to evaluate the outlined feature extraction techniques. The presented research points to opportunities in automated identification within the lead user approach that further reduce the resource and time costs. peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=ctas20 ispartof: Technology Analysis & Strategic Management vol:29 issue:6 pages:642-654 status: published

As Biologically-Inspired Design is receiving more and more attention, methodologies and tools are developed to support the systematic bio-ideation process. However, few experiments have been conducted that objectively measure the impact of bio-ideation methods or tools on the design outcomes of creativity efforts. This paper investigates the impact of two biological stimuli conditions – using short natural-language descriptions accompanied by a photograph of the involved biological system (1) or accompanied by a graphical illustration of the biological solution principle (2) – on the variety of the generated idea set. Hereto, biological strategies from one relevant functional class of AskNature’s Biomimicry Taxonomy are used as stimuli and their impact is quantified. Participants, 59 students divided into three groups, are all submitted to the no tool condition for a first design challenge from which the intended balancing effect of random group assignment is verified. During the second and third challenge, one group remains a control group and two groups receive one of the AskNature stimuli variants. The results show variable success for increasing variety – ranging from status quo to a 108.2% increase in variety at the physical principle level – indicating that using a functional category from AskNature has the potential to support conceiving more dissimilar idea set on the most abstract levels of the genealogy tree. However such performance is not guaranteed for each challenge. ispartof: pages:173-178 ispartof: Procedia CIRP vol:39 pages:173-178 ispartof: Structured Innovation with TRIZ in Science and Industry: Creating Value for Customers and Society location:Berlin date:26 Oct - 29 Oct 2015 status: published

© 2017 Much work on sustainable design has focused on product manufacture/assembly and end of life. Gains in products’ technical efficiency address the use phase, but how these products are used clearly affects resource consumption. This paper describes two main approaches to reduce resource consumption during product life. Firstly, interventions aim to change user behavior, through information and feedback, as well as physical product affordances abstracted from lead users to guide or steer users toward the desired behavior. Secondly, automatic adjustment of product systems performance levels based on personal user profiles and anticipated usage is implemented using artificial intelligence techniques. ispartof: CIRP Annals. Manufacturing Technology vol:66 issue:2 pages:635-658 status: published

Systematically developing innovative products demands effective idea generation methods. The effectiveness can be verified based on a set of metrics, of which the variety metric is one. It is demonstrated that this metric exhibits several shortcomings, such as the lack of level-based measurements, and arbitrarily defined level weights. The currently applied variety metrics, furthermore, do not measure the degree of uniformness of the distribution of ideas over nodes on an abstraction level. A level-based, correctly normalized variety metric which accounts for the degree of uniformness of the distribution of concepts over nodes, is proposed, and is shown to resolve the above issues. ispartof: Design Studies vol:34 issue:2 pages:243-263 status: published

As more and more people are increasingly turning to nature for design inspiration, tools and methodologies are developed to support the systematic bioideation process. State-of-the-art approaches struggle with expanding their knowledge bases because of interactive work required by humans per biological strategy. As an answer to this persistent challenge, a scalable search for systematic biologically inspired design (SEABIRD) system is proposed. This system leverages experience from the product aspects in design by analogy tool that identifies candidate products for between-domain design by analogy. SEABIRD is based on two conceptual representations, product and organism aspects, extracted from, respectively, a patent and a biological database, that enable leveraging the ever growing body of natural-language biological texts in the systematic bioinspired design process by eliminating interactive work by humans during corpus expansion. SEABIRD's search is illustrated and validated with three well-known biologically inspired design cases.

Single point incremental forming (SPIF) is an emerging application in sheet metal prototyping and small batch production, which enables dieless production of sheet metal parts. This research area has grown in the last years, both experimentally and numerically. However, numerical investigations into SPIF process need further improvement to predict the formed shape correctly and faster than current approaches. The current work aims the use of an adaptive remeshing technique, originally developed for shell and later extended to 3D “brick” elements, leading to a Reduced Enhanced Solid-Shell formulation. The CPU time reduction is a demanded request to perform the numerical simulations. A two-slope pyramid shape is used to carry out the numerical simulation and modelling. Its geometric difficulty on the numerical shape prediction and the through thickness stress behaviour are the main analysis targets in the present work. This work confirmed a significant CPU time reduction and an acceptable shape prediction accuracy using an adaptive remeshing method combined with the selected solid-shell element. The stress distribution in thickness direction revealed the occurrence of bending/unbending plus stretching and plastic deformation in regions far from the local deformation in the tool vicinity. ispartof: International Journal of Material Forming vol:9 issue:3 pages:383-394 ispartof: location:AUSTRALIA, Melbourne status: published

Patent repositories are considered as a state of the art in innovation efforts for specific product categories. Using text mining techniques on selected word categories in such repositories, complemented by a dimensional reduction method, generic product aspects are identified, allowing systematic quantification of the development state of product categories. The derived product profiles are applied for systematic identification of product categories that can contribute to the further development of selected product aspects for a product of interest. The effectiveness of this methodology was experimentally validated, demonstrating the significance of the proposed design-by-analogy approach based on the described product aspect analysis. © 2011 CIRP. ispartof: CIRP Annals. Manufacturing Technology vol:60 issue:1 pages:203-206 status: published

During problem solving, TRIZ users map a specific problem to a generic problem, solve it via TRIZ tools, and map back to a specific solution, a process relying heavily on their TRIZ skills. To aid less skilled users, a methodology and algorithm are proposed that, through identification of specific word categories in patents, analysis of term-term correlation data, and data mining techniques, automatically identify similar products, and properties relating or differentiating products. This algorithm can quantifiably guide creativity efforts and aid in patent portfolio management. © 2011 Published by Elsevier Ltd. ispartof: pages:83-88 ispartof: Proceedings of the ETRIA TRIZ Future 2008 vol:9 pages:83-88 ispartof: ETRIA TRIZ Future 2008 location:Twente, Nederland date:5 Nov - 7 Nov 2008 status: published

The vital importance of innovation on enterprises, and by extension, economies is often expressed as innovate or vegetate and innovate or evaporate . However, these expressions provide no insight on how to innovate, or on how to be inventive. The creative spark necessary for this kind of inventive thinking is typically thought of as situated in the realm of the human mind. Computers programs and algorithms can however support creativity by providing stimuli in different forms, e.g. random words, function databases, or previously documented solutions. This dissertation aims at stretching the boundaries of the level of support that algorithms bring to creative product development, i.e. the development of novel and useful products. The approach taken in this dissertation is to propose stimuli based on patent databases, which contain a vast number of previously documented solutions. Theunderlying assumption is that similar creative solutions might already have been implemented in a different application domain. The recollection of similar solutions over all application domains is not an easy task for humans. In contrast, computers excel at this kind of processing given that the data is in a suitable format, leading to the formulation of the first research goal: Research Goal 1: The development of history-based ideation methods, and automatic and scalable supporting algorithms applicable on patent databases, which are aimed at increasing the novelty and usefulness of the creative outcome of engineers and designers.Often ideation methods adopted in industry are not thoroughly scrutinized. In this respect, the increase of novelty and usefulness aimed for in Research Goal 1 is also too vague. An in-depth quantitative evaluation is needed to understand the effect of the proposed ideation method, as made explicit in the second research goal: Research Goal 2: The development of an experimental test method basedon ideation effectiveness metrics, which can be used to provide quantitativeevidence of the effect of the developed ideation method and algorithms.The structure of the dissertation is subdivided in two parts. The first part addresses Research Goal 1, and describes PAnDA (Products Aspects in Design-by-Analogy), being the method and algorithms developed in order to support engineers and designers by proposing cross-domain candidate products for Design-by-Analogy based on the textual extraction of a patent corpus. The second part addresses Research Goal 2. This part describes the metrics used in the quantitative evaluation, being the quantity, quality, novelty and variety, and furthermore proposes several refinements to the latter two. The novelty metric is refined to allow for the evaluation of systematic ideation methods. For both the variety and novelty metrics, level-based analyses are proposed in order to understand the effects of an ideation method. The variety metric is furthermore refined to account for the distribution of concepts on each abstraction level. Based on these refined metrics, the second part furthermore describes the experimental setup, and analysis of the results, together forming a framework which enabled the in-depth evaluation of the ideation method proposed in the first part.The contributions from the first part, describing the PAnDA tool, to the state of the art are: Automated: PAnDA is an ideation method based on large external sources of data needing no manual intervention to add products. Scalable: PAnDA scales well, as adding patents can be accomplished by folding-in techniques. Domain relatedness: PAnDA differentiates and informs the user whether the proposed products are inter-domain or cross-domain. High novelty, same technical feasibility: PAnDA increases the novelty of the generated concepts by up to 56%, while not reducing the technical feasibility.For the second part, which describes the metrics, experimental setup and analyses of the results, the contributions to the state of the art are: Novelty: The refinement to the novelty metric allows it to be applied to systematic and priming ideation methods. Variety: The refined variety metric accounts for the distribution of concepts over ideas on each abstraction level. In-depth analyses: This dissertation provides an in-depth understanding of the quantitative results of an ideation method. As such, it can serve as areference framework for the testing of other ideation methods. status: published

Like most front-end design methodologies, TRIZ is characterized by the need of an abstraction level to apply the methodology. Users of these methodologies rely on intrinsic skills to map a specific situation to a abstracted one, analyze it through the methodology, and, if applicable, map it back to a specific situation. A methodology and algorithm are proposed that eliminate this subjective and difficult to perform mapping by formalizing automatically identified, fine-grained product dimensions or Aspects. These Aspects can be applied in idea generation and problem solving contexts, e.g. building a function database, performing trends analysis and searching for similar products. © 2011 Published by Elsevier Ltd. ispartof: pages:323-336 ispartof: Proceedings of the ETRIA TRIZ Future 2009 vol:9 pages:323-336 ispartof: ETRIA TRIZ Future 2009 location:Timisoara, Romenia date:4 Nov - 6 Nov 2009 status: published

© Cranfield University 2009. TRIZ emerged from systematic analysis of patents, a process involving the mapping of innovative patents to extracted generic problems and generic inventive principles. During problem solving, TRIZ users, relying on their TRIZ skills, map their specific problem to a generic problem, solve it via TRIZ tools, and map back to a specific solution. A methodology and algorithm are proposed that, through identification of specific word categories in patents, analysis of term-term correlation data, and data mining techniques, automatically identify similar products, and properties relating or differentiating products. This algorithm can quantifiably guide creativity efforts and aid in patent portfolio management. ispartof: pages:30-31 ispartof: Proceedings of the 19th CIRP Design Conference – Competitive Design pages:30-31 ispartof: CIRP Design Conference 2009 location:Cranfield, United Kingdom date:30 Mar - 31 Mar 2009 status: published