Michael E. Helms

Cognitive, collaborative, conceptual and creative - Four characteristics of the next generation of knowledge-based CAD systems: A study in biologically inspired design

We envision that the next generation of knowledge-based CAD systems will be characterized by four features: they will be based on cognitive accounts of design, and they will support collaborative design, conceptual design, and creative design. In this paper, we first analyze these four dimensions of CAD. We then report on a study in the design, development and deployment of a knowledge-based CAD system for supporting biologically inspired design that illustrates these four characteristics. This system, called DANE for Design by Analogy to Nature Engine, provides access to functional models of biological systems. Initial results from in situ deployment of DANE in a senior-level interdisciplinary class on biologically inspired design indicates its usefulness in helping designers conceptualize design of complex systems, thus promising enough to motivate continued work on knowledge-based CAD for biologically inspired design. More importantly from our perspective, DANE illustrates how cognitive studies of design can inform the development of CAD systems for collaborative, conceptual, and creative design, help assess their use in practice, and provide new insights into human interaction with knowledge-based CAD systems.

A content account of creative analogies in biologically inspired design

Abstract The growing movement of biologically inspired design is driven in part by the need for sustainable development and in part by the recognition that nature could be a source of innovation. Biologically inspired design by definition entails cross-domain analogies from biological systems to problems in engineering and other design domains. However, the practice of biologically inspired design at present typically is ad hoc, with little systemization of either biological knowledge for the purposes of engineering design or the processes of transferring knowledge of biological designs to engineering problems. In this paper we present an intricate episode of biologically inspired engineering design that unfolded over an extended period of time. We then analyze our observations in terms of why, what, how, and when questions of analogy. This analysis contributes toward a content theory of creative analogies in the context of biologically inspired design.

DANE: Fostering Creativity in and through Biologically Inspired Design

In this paper, we present an initial attempt at systemizing knowledge of biological systems from an engineering perspective. In particular, we describe an interactive knowledge-based design environment called DANE that uses the Structure-Behavior-Function (SBF) schema for capturing the functioning of biological systems. We present preliminary results from deploying DANE in an interdisciplinary class on biologically inspired design, indicating that designers found the SBF schema useful for conceptualizing complex systems.

Compound Analogical Design: Interaction between Problem Decomposition and Analogical Transfer in Biologically Inspired Design

Biologically inspired design (BID) can be viewed as an example of analogical design from a cognitive standpoint. Existing models of analogical design cannot fully account for the generation of complex solutions in BID, especially those which contain compound solutions. In this paper we develop a conceptual framework of compound analogical design that explains the generation of compound solutions in design through opportunistic interaction of two related processes: analogy and problem decomposition. We also present our study of BID and apply this framework to analyze three sample designs that contained compound solutions.

Nature of creative analogies in biologically inspired innovative design

Analogy is a fundamental process of creativity. Biologically inspired design by definition entails cross-domain analogies, and in practice has led to many innovative designs. Thus, biological inspired design is an ideal domain for studying creative analogies. In this paper, we describe an intricate episode of biologically inspired design that unfolded over an extended period of time. We then analyze the episode in terms of Why, What, How and When questions of analogy. This analysis provides a content theory of creative analogies in biologically inspired design.

Analogical problem evolution in biologically inspired design

Conceptual design typically entails co-evolution of the design problem and the design solution: initial problem formulations lead to preliminary solutions; incremental changes in the proposed solution lead to new insights into the design problem, and so on. In this paper, we describe a complementary process: problem evolution using analogies to already existing design cases. In particular, we present a case study in the context of biologically inspired design that inspects the evolution of an ill-defined design problem from inception to conceptual design. This case study demonstrates three important aspects of problem evolution from inception: first, significant problem evolution may occur independent of the generation of a new design solution for that problem; second, existing solutions to related problems serve as analogies that influence the way in which the problem is formulated; and third, the use of existing solutions from different domains, for example from existing biological solutions to engineering design problems, generates value not only by offering both potentially innovative solutions but also by changing the formulation of the problem itself.

Information-Processing Theories of Biologically Inspired Design

Starting from in situ studies, we develop an information-processing theory of biologically inspired design. We compare our theory with two popular theories of biologically inspired design: Biomimicry 3.8 Institute’s Design Spiral and Vincent et al.’s BioTRIZ. While Design Spiral and BioTRIZ are normative and prescriptive, our information-processing theory provides a descriptive and explanatory account of the design paradigm. We examine if and how the process of biologically inspired design is different from that of other design paradigms beyond the differences between biological and technological systems. We posit that biologically inspired design appears to be a distinct design paradigm in part because it entails solution-based analogies in addition to the problem-driven analogies typical of other design paradigms.

BIOLOGICALLY INSPIRED DESIGN: A MACROCOGNITIVE ACCOUNT

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

Adaptive Evolution of Teaching Practices in Biologically Inspired Design

At Georgia Tech in 2005, we developed an interdisciplinary undergraduate semester-long course, biologically inspired design (BID), co-taught each year by faculty from biology and engineering. The objective of this chapter is to share our teaching experience with those interested in teaching such a course themselves. The specific curriculum of a BID course must depend on the student mix, the institutional context, and instructor goals. Therefore, rather than presenting a particular curriculum, we present key problems that we encountered in our 8 years of teaching and how we addressed them. We expect that any who try to teach such a course will face one or more of the same challenges, and we offer numerous pedagogical approaches that can be tailored to their specific circumstances. By describing our solutions, their consequences, and the extent to which they met our expectations, we also point out where tough student challenges still exist that are in need of attention from the community.

The Effect of Functional Modeling on Understanding Complex Biological Systems

Biologically inspired engineering design requires understanding of complex biological systems for use as analogues in engineering designs. In this study we seek to understand how functional representations, in particular Structure-BehaviorFunction (SBF) models, enable understanding complex biological systems. Results from this study indicate that SBF representations may enable more accurate inferences about biological systems for complex and abstract questions than purely textual, or textual and diagrammatic, representations. They also suggest that no one representation is best for all types of inferences.