This work presents a Set-Based Design inspired approach for generation, evaluation and reduction of a solution space of alternative product concepts. Also, the aspect of how to implement the process in an industrial environment was investigated. The hypothesis, confirmed by case studies, is that it can be done using existing methods like Enhanced functional modelling, brainwriting, the Gallery method, Axiomatic Design, causal diagrams and Pugh matrices. The method can be successfully introduced in a timeframe of a few working days and support development engineers in the concept design phase.

This study presents a search method for a solution space that aligns with a designer's design intent. The proposed method uses multiobjective optimization to determine the size of the narrowed solution space and the weakness of the constraint relationships between the design variables. The suitability of the proposed method is tested by applying it to the design problem of an electric motor for an EV, aiming to provide designers with solution spaces that offer a high degree of freedom in the later design stages and that have weaker constraint relationships among the design variables.

Set-based concurrent engineering (SBCE), a process that develops sets of many design candidates for each subproblem throughout a design project, proposes several benefits compared to point-based processes, where only one design candidate for each subproblem is chosen for further development. These benefits include reduced rework, improved design quality, and retention of knowledge to use in future projects. Previous studies that introduce SBCE in practice achieved success and had very positive future outlooks, but SBCE encounters opposition because its core procedures appear wasteful as designers must divide their time among many designs throughout the process, most of which are ultimately not used. The impacts of these procedures can be explored in detail through open-source computational tools, but currently few exist to do this. This work introduces the Point/Set-Organized Research Teams (PSORT) modeling platform to simulate and analyze a set-based design process. The approach is used to verify statements made about SBCE and investigate its effects on project quality. Such an SBCE platform enables process exploration without needing to commit many projects and resources to any given design.

Set-based design (SBD), sometimes referred to as set-based concurrent engineering (SBCE), has emerged as an important component of lean product development (LPD) with all researchers describing it as a core enabler of LPD. Research has explored the principles underlying LPD and SBCE, but methodologies for the practical implementation need to be better understood. A review of SBD is performed in this article in order to discover and analyse the key aspects to consider when developing a model and methodology to transition to SBCE. The publications are classified according to a new framework, which allows us to map the topology of the relevant SBD literature from two perspectives: the research paradigms and the coverage of the generic creative design process (Formulation–Synthesis–Analysis–Evaluation–Documentation–Reformulation). It is found that SBD has a relatively low theoretical development, but there is a steady increase in the diversity of contributions. The literature abounds with methods, guidelines and tools to implement SBCE, but they rarely rely on a model that is in the continuum of a design process model, product model or knowledge-based model with the aim of federating the three Ps (People–Product–Process) towards SBCE and LPD in traditional industrial contexts.

During the early stages of any system design, a thorough exploration of the design space can prove to be challenging and computationally expensive. The challenges are further exacerbated when dealing with complex systems, such as an aircraft, due to the high dimensionality of their design space. Arising from the Toyota Product Development System, set-based design allows parallel evaluation of multiple alternative configurations in the early design stages. At the same time, optimisation methods can be employed at later stages to fine-tune the engineering characteristics of design variants. Presented in this paper, is the Augmented set-based Design and OPTimisation (ADOPT) Framework that introduces a novel methodology for integrating the two areas. This allows for a thorough design-space exploration while ensuring the optimality of the selected designs. The framework has been developed using a process-independent and tool-agnostic approach so that it can be applied to the design process of varying kinds of systems. To demonstrate the implementation and potential benefits, the framework has been applied to the design of a generic aircraft fuel system. The results from the case study and the framework itself are discussed, with a number of areas for further development and future work being identified and presented.

Prior research has identified set-based design as a method that accounts for the high level of uncertainty that is associated with the design of innovative products or systems. Rather than precisely specifying a system architecture in the early design stages, set-based design builds on designing a system and its architecture in an evolutionary way. The literature on set-based design has studied how a system's design evolves by moving from a number of optional design ideas to the final system through gradually eliminating unfeasible design ideas and continually developing design ideas for which engineers increasingly establish feasibility. However, little is known about how firms set up the design process and the organization to successfully create new products with set-based design. Our research contributes to closing this gap. First, we study how firms determine the number (i.e., portfolio) of design ideas to pursue, an important step of the early design process. Second, we study how firms organize for set-based design by assigning teams to develop design ideas and eventually design a system's architecture. Our research uses an exploratory case study approach, investigating five cases in three different firms. First, we find that the early design process is characterized by the absence of formal idea evaluation and selection. Instead, firms start to pursue all initially created design ideas, evaluating and selecting them in an evolutionary manner as the design project progresses. Second, we identify two organizational approaches associated with set-based design: assign one team to pursue all ideas or assign one team per design idea.

Interval arithmetic has been extensively applied to systems of linear equations by the interval matrix arithmetic community. This paper demonstrates through simple examples that some of this work can be viewed as particular instantiations of an abstract “design operation,” the RANGE operation of the Labeled Interval Calculus formalism for inference about sets of possibilities in design. These particular operations promise to solve a variety of design problems that lay beyond the reach of the original Labeled Interval Calculus. However, the abstract view also leads to a new operation, apparently overlooked by the matrix mathematics community, that should also be useful in design; the paper provides an algorithm for computing it.

This paper defines, develops algorithms for, and illustrates the utility in design of a class of mathematical operations. These accept as inputs a system of linear constraint equations, Ax = b, an interval matrix of values for the coefficients, A, and an interval vector of values for either x or b. They return a set of values for the “domain” of the other vector, in the sense that all combinations of the output vector values set and values for A, when inserted into the constraint equation, correspond to values for the input vector that lie within the input interval. These operations have been mostly overlooked by the interval matrix arithmetic community, but are mathematically interesting and useful in the design, for example, of structures.

This paper defines, develops algorithms for, and illustrates the design use of a class of mathematical operations. These operations accept as inputs a system of linear constraint equations, Ax = b, an interval matrix of values for the coefficients A, and an interval vector of values for either x or b. They return a set of values for the other variable that is “sufficient” in this sense. Suppose that ◯ is an interval of input vectors, and  an interval matrix. Then, one Sufficient-Points operation returns a set of vectors ~ such that for each b in ~, the set of x values that can be produced by inserting all the values of  into Ax = b is a superset of the input vector x. These operations have been partly overlooked by the interval matrix mathematics community, but are mathematically interesting and useful in the design, for example, of circuits.

MarCon (Market-based Constraints) applies market-based control to distributed constraint problems. It offers a new approach to distributing constraint problems that avoids challenges faced by current approaches in some problem domains, and it provides a systematic method for applying markets to a wide array of problems. Constraint agents interact with one another via the variable agents in which they have a common interest, using expressions of their preferences over sets of assignments. Each variable integrates this information from the constraints interested in it and provides feedback that enables the constraints to shrink their sets of assignments until they converge on a solution. MarCon originated in a system for supporting human product designers, and its mechanisms are particularly useful for applications integrating human and machine intelligence to explore implicit constraints. MarCon has been tested in the domain of mechanical design, in which its set-narrowing process is particularly useful.