This paper describes the findings of an experiment on how different engineers understand notions of function and functional breakdown in the context of design by modification. The experiment was conducted with a homogenous group of 20 design engineers, who had all received the same education. The subjects were asked to analyze how a hydraulic pump works and summarize their understanding in a function tree. The subjects were given either the hydraulic pump itself (with part of its casing removed) or a maintenance drawing that showed a section cut of the pump. This paper shows typical outputs of the designers. It discusses the different notions of function that the subjects had and the differences in the function trees they generated. The paper focuses an eight detailed analyses to show the range of approaches the subjects took.

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.

Currently available computer-aided design tools provide strong support for the later stages of product development processes where the structure and shape of the design have been fixed. Support for earlier stages of product development, when both the structure and shape of the design are still fluid, demands conceptual design tools that support designers' ways of thinking and working, and enhance creativity, for example, by offering design alternatives, difficult or not, possible without the use of such tools. The potential of spatial grammars as a technology to support such design tools has been demonstrated through experimental research prototypes since the 1970s. In this paper, we provide a review of recent spatial grammar implementations, which were presented in the Design Computing and Cognition 2010 workshop on which this paper is based, in the light of requirements for conceptual design tools and identify future research directions in both research and design education.

The natural world provides numerous cases for analogy and inspiration in engineering design. During the early stages of design, particularly during concept generation when several variants are created, biological systems can be used to inspire innovative solutions to a design problem. However, identifying and presenting the valuable knowledge from the biological domain to an engineering designer during concept generation is currently a somewhat disorganized process or requires extensive knowledge of the biological system. To circumvent the knowledge requirement problem, we developed a computational approach for discovering biological inspiration during the early stages of design that integrates with established function-based design methods. This research defines and formalizes the information identification and knowledge transfer processes that enable systematic development of biologically inspired designs. The framework that supports our computational design approach is provided along with an example of a smart flooring device to demonstrate the approach. Biologically inspired conceptual designs are presented and validated through a literature search and comparison to existing products.

We present a multimodal spatial data access framework designed to serve the informational and computational requirements of architectural design assistance systems that are intended to provide intelligent spatial decision support and analytical capabilities. The framework focuses on multiperspective semantics, qualitative and artifactual spatial abstractions, and industrial conformance and interoperability within the context of the industry foundation classes. The framework provides qualitative and cognitively adequate representational mechanisms, and the formal interpretation of the structural form of indoor spaces that are not directly provided by conventional computer-aided design based or quantitative models of space. We illustrate the manner in which these representations directly provide the spatial abstractions that are needed to enable the implementation of intelligent analytical capabilities in design assistance tools. We introduce the framework, and also provide detailed use cases that illustrate the usability of the framework and the manner of its utilization within architectural design assistance systems.

Reflective actions in collaborative design can potentially improve design performance and results. This paper quantitatively reexamines the relationships between reflective activities and design performance during the collaborative design process in terms of reflection in action. Twenty sets of protocol data were encoded by a modified version of Valkenburg and Dorst's coding scheme. Using statistical testing, the relationship between the design performance and the number of activities plus the transitions was examined. A significant statistical correlation was found between the percentage of mature framing (setting up of a desired goal with sufficient follow-ups) and the overall performance. These quantitative results verify the qualitative findings of the previous study.

The tool switching problem (ToSP) is well known in the domain of flexible manufacturing systems. Given a reconfigurable machine, the ToSP amounts to scheduling a collection of jobs on this machine (each of them requiring a different set of tools to be completed), as well as the tools to be loaded/unloaded at each step to process these jobs, such that the total number of tool switches is minimized. Different exact and heuristic methods have been defined to deal with this problem. In this work, we focus on memetic approaches to this problem. To this end, we have considered a number of variants of three different local search techniques (hill climbing, tabu search, and simulated annealing), and embedded them in a permutational evolutionary algorithm. It is shown that the memetic algorithm endowed with steepest ascent hill climbing search yields the best results, performing synergistically better than its stand-alone constituents, and providing better results than the rest of the algorithms (including those returned by an effective ad hoc beam search heuristic defined in the literature for this problem).