Is biologically inspired design only an analogical transfer from biology to engineering? Actually, nature does not always bring “hands-on” solutions that can be analogically applied in classic engineering. Then, what are the different operations that are involved in the bioinspiration process and what are the conditions allowing this process to produce a bioinspired design? In this paper, we model the whole design process in which bioinspiration is only one element. To build this model, we use a general design theory, concept–knowledge theory, because it allows one to capture analogy as well as all other knowledge changes that lead to the design of a bioinspired solution. We ground this model on well-described examples of biologically inspired designs available in the scientific literature. These examples include Flectofin®, a hingeless flapping mechanism conceived for façade shading, and WhalePower technology, the introduction of bumps on the leading edge of airfoils to improve aerodynamic properties. Our modeling disentangles the analogical aspects of the biologically inspired design process, and highlights the expansions occurring in both knowledge bases, scientific (nonbiological) and biological, as well as the impact of these expansions in the generation of new concepts (concept partitioning). This model also shows that bioinspired design requires a special form of collaboration between engineers and biologists. Contrasting with the classic one-way transfer between biology and engineering that is assumed in the literature, the concept–knowledge framework shows that these collaborations must be “mutually inspirational” because both biological and engineering knowledge expansions are needed to reach a novel solution.

User-centered approaches to design can guide teams toward an understanding of users and aid teams in better posing design problems. This paper investigates the role of user-centered design approaches in design process and outcome within the context of design team projects. The value of interaction with users is examined at several stages throughout the design process. The influence of user-centered design on the performance of design teams is also explored. Results suggest that the quantity of interactions with users and time spent interacting with users alone is not linked with better design outcome, but that iterative evaluation of concepts by users may be of particular value to design prototypes. Suggestions are made based on the reflections from the authors after conducting this study.

Rationale research in software development is a challenging area because although there is no shortage of advocates for its value, there is also no shortage of reasons for why rationale is unlikely to be captured in practice. Despite more than 30 years of research there still remains much uncertainty: how useful are the potential benefits and how insurmountable are the barriers? Will the value of the rationale (design and otherwise) justify the cost of collecting it? Although there have been numerous rationale research projects, many, if not most, received little or no empirical evaluation. There also have not been many studies examining what the needs are of the practitioners who would be supported by the rationale. This article discusses the “doom and gloom” predictions of rationale's failure, provides a survey of evaluations of rationale systems, and discusses what we hope is a brighter outlook for rationale research in the future. There are development standards and synergistic research areas that may help with rationale research and its acceptance in the software community with which we should be working. This article also presents the results of a pilot survey of software developers who were asked how they would envision using rationale and what they believe the most important barriers are. Although some results were as expected, there were also some surprises. Research on technology transfer indicates that, among other things, to transition successfully from research into practice we need to understand the need that is being met and demonstrate the value of our approach. Until we have determined how our work is needed by the people we are trying to help we will remain researching under uncertainty.

The development of a fuzzy wavelet neural network (FWNN) for the prediction of electricity consumption is presented. The fuzzy rules that contain wavelets are constructed. Based on these rules, the structure of FWNN-based system is described. The FWNN system is applied for modeling and prediction of complex time series. The gradient algorithm and genetic algorithm are used for learning of FWNN parameters. The developed FWNN is applied for prediction of electricity consumption. This process has high-order nonlinearity. The statistical data for the last 10 years are used for the development of FWNN prediction model. The effectiveness of the proposed system is evaluated with the results obtained from the simulation of FWNN-based prediction system and with the comparative simulation results of previous related models.

Present-day software applications are increasingly required to be “reuse-conscious” in terms of the operating platforms, topology, and evolutionary requirements. Traditionally, there has been much difficulty in communicating specialized knowledge like design intents, design recommendations, and design justifications in the discipline of software engineering. This paper presents a methodology based on the combination of design rationale and design patterns to design reusable software systems. Design rationale is the representation of the reasoning behind the design of an artifact. Design patterns are descriptions of communicating objects and classes that are customized to solve a general design problem in a particular context. The paper details the use of an explicit software development process to capture and disseminate the specialized knowledge (i.e., intents, recommendations, and justifications) that augments the description of the cases in a library (i.e., design patterns) during the development of software applications by heterogeneous groups. The importance of preserving and using this specialized knowledge has become apparent with the growing trend of combining the software development process with the product (i.e., software code). The importance of codifying corporate memory in this regard is also important considering the changing nature of the workplace, where more people are on contract. The information on how and why a software code was developed becomes essential for efficient and smooth continuity of the present software project as well as for reusing the code in future projects. It has become essential to capture the design rationale to develop and design software systems efficiently and reliably. The software prototype developed using the combined methodology will be used as a part of an integrated design environment for reusable software design. This environment supports collaborative development of software applications by a group of software specialists from a library of building block cases represented by design patterns.

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: novelty and usefulness. 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 creativity consistently across 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 consider novelty and usefulness as the necessary factors for creativity. It is found, however, that it is not possible to directly assess the usefulness of outcomes during the design process. Therefore, requirement satisfaction is used as a proxy for usefulness. We propose a creativity assessment method that uses novelty and requirement satisfaction as 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.

A precise market model for a well-defined class of distributed configuration design problems is presented. Given a design problem, the model defines a computational economy to allocate basic resources to agents participating in the design. The result of running these “design economies” constitutes the market solution to the original problem. After defining the configuration design framework, the mapping to computational economies and the results to date are described. For some simple examples, the system can produce good designs relatively quickly. However, analysis shows that the design economies are not guaranteed to find optimal designs, and some of the major pitfalls are identified and discussed. Despite known shortcomings and limited explorations thus far, the market model offers a useful conceptual viewpoint for analyzing distributed design problems.

Resilience is a key driver in the design of systems that must operate in an uncertain operating environment, and it is a key metric to assess the capacity for systems to perform within the specified performance envelop despite disturbances to their operating environment. This paper describes a graph spectral approach to calculate the resilience of complex engineered systems. The resilience of the design architecture of complex engineered systems is deduced from graph spectra. This is calculated from adjacency matrix representations of the physical connections between components in complex engineered systems. Furthermore, we propose a new method to identify the most vulnerable components in the design and design architectures that are robust to transmission of failures. Nonlinear dynamical system and epidemic spreading models are used to compare the failure propagation mean time transformation. Using these metrics, we present a case study based on the Advanced Diagnostics and Prognostics Testbed, which is an electrical power system developed at NASA Ames as a subsystem for the ramp system of an infantry fighting vehicle.

This paper introduces a rigorous framework for function modeling of complex multidisciplinary systems based on the system state flow diagram (SSFD). The work addresses the need for a consistent methodology to support solution-neutral function-based system decomposition analysis, facilitating the design, modeling, and analysis of complex systems architectures. A rigorous basis for the SSFD is established by defining conventions for states and function definitions and a representation scheme, underpinned by a critical review of existing literature. A set of heuristics are introduced to support the function decomposition analysis and to facilitate the deployment of the methodology with strong practitioner guidelines. The SSFD heuristics extend the existing framework of Otto and Wood (2001) by introducing a conditional fork node heuristic, to facilitate analysis and aggregation of function models across multiple modes of operation of the system. The empirical validation of the SSFD function modeling framework is discussed in relation to its application to two case studies: a benchmark problem (glue gun) set for the engineering design community; and an industrial case study of an electric vehicle powertrain. Based on the evidence from the two case studies presented in the paper, a critical evaluation of the SSFD function modeling methodology is discussed based on the function benchmarking framework established by Summers et al. (2013), considering the representation, modeling, cognitive, and reasoning characteristics. The significance of this paper is that it establishes a rigorous reference framework for the SSFD function representation and a consistent methodology to guide the practitioner with its deployment, facilitating its impact to industrial practice.

Sketching is a natural and intuitive communication tool used for expressing concepts or ideas which are difficult to communicate through text or speech alone. Sketching is therefore used for a variety of purposes, from the expression of ideas on two-dimensional (2D) physical media, to object creation, manipulation, or deformation in three-dimensional (3D) immersive environments. This variety in sketching activities brings about a range of technologies which, while having similar scope, namely that of recording and interpreting the sketch gesture to effect some interaction, adopt different interpretation approaches according to the environment in which the sketch is drawn. In fields such as product design, sketches are drawn at various stages of the design process, and therefore, designers would benefit from sketch interpretation technologies which support these differing interactions. However, research typically focuses on one aspect of sketch interpretation and modeling such that literature on available technologies is fragmented and dispersed. In this paper, we bring together the relevant literature describing technologies which can support the product design industry, namely technologies which support the interpretation of sketches drawn on 2D media, sketch-based search interactions, as well as sketch gestures drawn in 3D media. This paper, therefore, gives a holistic view of the algorithmic support that can be provided in the design process. In so doing, we highlight the research gaps and future research directions required to provide full sketch-based interaction support.

This paper focuses on computer-based generative methods for layout problems in architecture and urban planning with special regard for the hierarchical structuring of layout elements. The generation of layouts takes place using evolutionary algorithms, which are used to optimize the arrangement of elements in terms of overlapping within a given boundary and the topological relations between them. In this paper, the approach is extended by a data structure that facilitates the hierarchical organization of layout elements making it possible to structure and organize larger layout problems into subsets that can be solved in parallel. An important aspect for the applicability of such a system in the design process is an appropriate means of user interaction. This depends largely on the calculation speed of the system and the variety of viable solutions. These properties are evaluated for hierarchical as well as for nonhierarchical structured layout problems.

This research proposes a procedure for solving the multiresponse problem in the Taguchi method utilizing two data envelopment analysis (DEA) approaches, including comparisons of efficiency between different systems (CEBDS) and bilateral comparisons. In this procedure, each experiment in Taguchi's orthogonal array (OA) is treated as a decision-making unit (DMU) with the multiresponses as the inputs and outputs for all DMUs. For each factor of OA, the DMUs are divided into groups, each at the same factor level. Then, DMU's efficiency is separately evaluated by the CEBDS approach and the bilateral comparisons approach for each factor. The level efficiency, or the average of the efficiencies obtained by the CEBDS and the bilateral comparisons approaches for that factor level, is then used to determine the optimal factor levels for multiresponses. Three case studies are provided for illustration; in all, the proposed procedure provides the largest total anticipated improvements. Hence, it should be considered the most effective among all approaches applied in the case studies, including principal component analysis, DEA-based ranking approach, and others. In addition, the proposed procedure is more effective and requires less computational effort when the DMU's efficiency is evaluated by the bilateral comparisons approach instead of the CEBDS approach. In conclusion, the proposed procedure will provide great assistance to practitioners for solving the multiresponse problems in manufacturing applications on the Taguchi method.

Studies of creativity have tended to focus on isolated individuals, under the assumption that it can be defined as a characteristic of an extraordinary person, product, or process. Existing computational models of creative behavior have inherited this emphasis on independent generative processes. However, an increasing multidisciplinary consensus regards creativity as a systems property, and extends the focus of inquiry to include the interaction between generative individuals and evaluative social groups. To acknowledge the complementarity of evaluative processes by social groups, experts, and peers, this paper presents experimentation with a framework of design as a social activity. This model is used to inspect phenomena associated with creativity in the interaction between designers and their societies. In particular, this paper describes the strength of social ties as a mechanism of social organization, and explores its potential relation to creativity in a computational social simulation. These experiments illustrate ways in which the role of designers as change agents of their societies can be largely determined by how the evaluating group self-organizes over time. A key potential implication is that the isolated characteristics of designers may be insufficient to formulate conclusions about the nature and effects of their behavior. Instead, causality could be attributed to situational factors that define the relationship between designers and their evaluators.

More than 40 years after Rittel and Webber published the first articles on the theory of wicked problems this theory has been applied to a wide range of fields involved in real-world problem solving. Interest in the theory seems greater than ever. This has led to an interest in rethinking the theory. A number of authors do this by imposing interpretations on the theory that are incompatible with each other and with the statements of the theory's authors. We agree that it is time to critically reexamine the theory and rethink what implications it has for design. However, rather than imposing an incompatible interpretation, our approach is see what new conclusions can be drawn from a systematic and critical examination of what Rittel and Webber actually said. This reexamination of their specific claims and arguments is what we call untangling wicked problems. From this untangling, we derive new conclusions about how designers should tackle wicked problems and how design rationale can aid them in doing so.

We show that the usual notion of constraint propagation is but one of a number of similar inferences useful in quantitative reasoning about physical objects. These inferences are expressed formally as rules for the propagation of ‘labeled intervals’ through equations. We prove the rules' correctness and illustrate their utility for reasoning about objects (such as motors or transmissions) which assume a continuum of different states. The inferences are the basis of a ‘mechanical design compiler’, which has correctly produced detailed designs from ‘high level’ descriptions for a variety of power transmission and temperature sensing systems.

The knowledge used in the design of engineering systems includes: understanding systems and their components, and the understanding implications of design decisions on other decisions and further problem decomposition This paper presents design as a process and then characterizes the knowledge used in synthesizing design alternatives. A knowledge based approach to design synthesis is proposed, followed by a description of the implementation of a domain independent synthesis framework. The implementation is further illustrated by an example application to structural design.

Massive open online courses, online tutoring systems, and other computer homework systems are rapidly changing engineering education by providing increased student feedback and capitalizing upon online systems' scalability. While online homework systems provide great benefits, a growing concern among engineering educators is that students are losing both the critical art of sketching and the ability to take a real system and reduce it to an accurate but simplified free-body diagram (FBD). For example, some online systems allow the drag and drop of forces onto FBDs, but they do not allow the user to sketch the FBDs, which is a vital part of the learning process. In this paper, we discuss Mechanix, a sketch recognition tool that provides an efficient means for engineering students to learn how to draw truss FBDs and solve truss problems. The system allows students to sketch FBDs into a tablet computer or by using a mouse and a standard computer monitor. Using artificial intelligence, Mechanix can determine not only the component shapes and features of the diagram but also the relationships between those shapes and features. Because Mechanix is domain specific, it can use those relationships to determine not only whether a student's work is correct but also why it is incorrect. Mechanix is then able to provide immediate, constructive feedback to students without providing final answers. Within this manuscript, we document the inner workings of Mechanix, including the artificial intelligence behind the scenes, and present studies of the effects on student learning. The evaluations have shown that Mechanix is as effective as paper-and-pencil-based homework for teaching method of joints truss analysis; focus groups with students who used the program have revealed that they believe Mechanix enhances their learning and that they are highly engaged while using it.

If a solvable problem is currently unsolved, then something important to a solution is most likely being overlooked. From this simple observation we derive the obscure features hypothesis: every innovative solution is built upon at least one commonly overlooked or new (i.e., obscure) feature of the problem. By using a new definition of a feature as an effect of an interaction, we are able to accomplish five things. First, we are able to determine where features come from and how to search for new ones. Second, we are able to construct mathematical arguments that the set of features of an object is not computably enumerable. Third, we are able to characterize innovative problem solving as looking for a series of interactions that produce the desired effects (i.e., the goal). Fourth, we are able to construct a precise problem-solving grammar that is both human and machine friendly. Fifth, we are able to devise a visual and verbal problem-solving representation that both humans and computers can contribute to as they help counteract each other's problem-solving weaknesses. We show how computers can counter some of the known cognitive obstacles to innovation that humans have. We also briefly discuss ways in which humans can return the favor. We conclude that a promising process for innovative problem solving is a human–computer collaboration in which each partner assists the other in unearthing the obscure features of a problem.

Generative specifications have been used to systematically codify established styles in several design fields including architecture and product design. We examine how designers explore new designs in the early stages of product development as they manipulate and interpret shape representations. A model of exploration is proposed with four types of shape descriptions (contour, decomposition, structure, and design) and the results of the exploration are presented. Generative rules are used to provide consistent stylistic changes first within a given decomposition and second through changing the structure. Style expresses both the analytical order of explanation and the synthetic complexity of exploration. The model of exploration is consistent with observations of design practice. The application of generative design methods demonstrates a logical pattern for early stage design exploration. The model provides the basis for tools to assist designers in exploring families of designs in a style and for following new interpretations that move the exploration from one family to another.