This study explores the construction, characterization, and measurement of the design space using a novel approach that centres on First Occurrences (FOs) and Re-Occurrences (ROs) as metrics. Expert architects' cognitive behaviours during the design process were investigated empirically to gain insights into design space evolution. Findings reveal a consistent generation and revisiting of ideas, signifying an ongoing development of the design space. Future research should incorporate diverse methodologies and broader participant sample for a more comprehensive understanding.

Understanding team diversity has become essential for modern-day organisations. This study explores the impact of knowledge diversity in design teams through computational simulations. By analysing design space characteristics, we study how diverse teams perform compared to less diverse counterparts. Results reveal that highly diverse teams exhibit increased efficiency, quicker convergence, and larger but sparser design spaces. This work contributes to understanding the impact of knowledge diversity in design teams and sets the stage for future systematic studies of diversity.

Combinatorial Design such as configuration design, design optioneering, component selection, and generative design, is common across engineering. Generating solutions for a combinatorial design task often involves the application of classical computing solvers that can either map or navigate design spaces. However, it has been observed that classical computing resource power-law scales with many design space models. This observation suggests classical computing may not be capable of modelling our future design space needs.

To meet future design space modelling needs, this paper examines quantum computing and the characteristics that enables its resources to scale polynomially with design space size. The paper then continues to present a combinatorial design problem that is subsequently represented, constrained and solved by quantum computing. The results of which are the derivation of an initial set of circuits that represent design space constraints. The study shows the game-changing possibilities of quantum computing as an engineering design tool and is the start of an exciting new journey for design research.

This paper synthesizes concepts from the design creativity and design optimization literatures to develop a conceptual descriptive model of trade-off situations in design. Using a set theory approach, a model of the design space is expanded to formalize the description of trade-offs as Pareto frontiers on this space. The modelling of design process and human biases and limitations on the structure of these design spaces explores the perceptions designers form of these design spaces. The model presented describes how altering the framing and formulation of the design space can be used to alter or bypass the original Pareto frontiers of that space, allowing trade-offs to be navigated outside of the original limitations.

Having no fundamental difficulties with Woodbury and Burrow's article, I explore some implications of their work based on my experience, and that of PhD students advised by me, with developing design support systems. I suggest that such systems need a distinct task layer on top of the computational layer, where the power of a system rests. I also express unease with some details of the article under review, in the hope of contributing to a wider discussion.

Design involves reasoning about descriptions of design artifacts, reasoning about design requirements, and reasoning about design process objectives (such as keeping to deadlines and available budget). Reasoning about these three aspects occurs during exploration, generation, and evaluation of partial design descriptions. Design space exploration involves exploration in all three related spaces: the space of partial descriptions of design artifacts, the space of design requirements, and the space of design process objectives. These spaces are vast. Explicit representation of the relations between elements in these three spaces provides the additional information needed to understand and reuse descriptions of partial design process traces, and to guide design exploration. In their Keynote Article, Woodbury and Burrow describe one of these spaces, namely, the space of design object descriptions, as a network of partial and intentional descriptions of design artifacts. The links between partial descriptions represent paths in design processes. Making the information compiled in these paths of exploration explicit, as proposed in this paper, extends the approach described by Woodbury and Burrow, increasing options for accessibility.

This paper examines the need for explicit representations of the design space, in response to Woodbury and Burrow. Specifically, their proposal for a particular search strategy, by means of which one can reuse past experiences explicitly represented by previously traversed paths, is examined. This is done by exploring issues with respect to design search and representation in general, while relating these to specific issues raised by Woodbury and Burrow. The paper concludes by suggesting that their arguments essentially point to devising an appropriate “programming language” for design.

The paper presents aspects of designer action that stress cognitive strategies for effective design problem solving, under the headings of exploration and representation. It proposes that links among design moves and shifts between design arguments are of prime importance in exploration and the design space should accommodate and expose them. The primacy of self-generated representations in the form of free-hand sketches and the role of arbitrary visual stimuli as supporting design reasoning is introduced. The expositions lead to the conclusion that the design space should be conceived as a multilevel and multifacet construct that supports on the spot experimentation and provides essential feedback not only regarding designs, but also concerning the process of designing.

In this paper, an optimal kinematic design method of a three translational DoFs parallel manipulator is presented. The design is based on the concept of performance chart, which can show the relationship between a criterion and design parameters graphically and globally. The normalization on the design parameters of the studied manipulator makes it possible that the design space, which is made up of the normalized parameters, is limited. The design space includes of all possible basic similarity manipulators (BSMs). As any one of the BSMs represents all of its similarity manipulators (SMs) in terms of performances, if one BSM is optimal, its SMs are optimized as well. The said optimal BSM is from the optimum region, which is the intersecting result of involved performance charts. In this paper, the related performance criteria are good-conditioning workspace (GCW), global conditioning index (GCI) and global stiffness index (GSI). As an applying example, a design result of the parallel manipulator with a desired task workspace is presented. The results of the paper are very useful for the design and application of a parallel manipulator.