System architecture and modularity decisions are inherent to preliminary concept design. Prior modularity research has considered minimizing interactions between modules and increasing the commonality among modular product variants. Effective approaches include function structure partitioning guidelines, affinity analysis, or matrix clustering algorithms. We consider here designs with field constraints, such as situations when elements cannot be placed in certain regions such as a high-temperature field, a high-pressure field, a high magnetic field, etc. which place constraints on modularity choices. Practical design guidelines are developed here for modularity considering field constraints. Two types of guidelines are proposed, field separation and concept generation. The field separation guidelines propose zonal boundaries within which system modules need be confined. The concept generation guidelines propose how to violate the field constraints through new concepts. Moving functionality from one side of a field boundary to the other is nontrivial and involves new concept generation for the modules to function at the higher or lower field values. The guidelines are defined and illustrated via multiple common examples as well as two extended case studies. We demonstrate the approach using field boundaries on an electric motor controller and on a medical contrast injector, and also use of fields to generated novel concepts. The guidelines support for modularity concept and embodiment decisions.

Modularity is an approach to manage the design of complex systems by partitioning and assigning elements of a concept to simpler subsystems according to a planned architecture. Functional-flow heuristics suggest possible modules that have been demonstrated in past products, but using them still leaves it to the designer to choose which heuristics make sense in a certain architecture. This constitutes an opportunity for a designer to take other constraints and objectives into account. With large complex systems, the number of alternative groupings of elements into modular chunks becomes exponentially large and some form of automation would be beneficial to accomplish this task. Clustering algorithms using the design structure matrix (DSM) representation search the space of alternative relative positioning of elements and present one ideal outcome ordering which “optimizes” a modularity metric. Beyond the problems of lack of interactive exploration around the optimized result, such approaches also partition the elements in an unconstrained manner. Yet, typical complex products are subject to constraints which invalidate the unconstrained optimization. Such architectural partitioning constraints include those associated with external force fields including electric, magnetic, or pressure fields that constrain some functions to perform or not perform in different regions of the field. There are also supplier constraints where some components cannot be easily provided with others. Overall, it is difficult to simply embed all objectives of modular thinking into one metric to optimize. We develop a new type of interactive clustering algorithm approach considering multiple objectives and partitioning constraints. Partitioning options are offered to a designer interactively as a sequence of clustering choices between elements in the architecture. A designer can incorporate constraints that determine the compatibility or incompatibility of elements by choosing among alternative groupings progressively. Our aim is to combine computational capability of clustering algorithms with the flexibility of manual approaches. Through applying these algorithms to a MRI machine injector, we demonstrate the benefits of interactive cooperation between a designer and modularity algorithms, where constraints can be naturally considered.

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Past work has demonstrated that simulating an extraordinary user scenario could have an impact on increasing designer empathy and creativity. It is likely, however, that an individual’s background could make a difference on how such simulated scenarios influence designers and how well the design method works. In this paper, we study the impact of demography and personal connection of the participants to any given simulated scenario versus their response to different empathic simulation workshops. With a variety of design tools and techniques available, understanding such influencing factors could help designers decide on the appropriate design tool for effective ideation. In this study, we investigated the effect of 81 (49 female and 32 male) users from three different workshops that simulated three different extraordinary user scenarios. Results of the study show that personal connection to a population being simulated significantly affects the impact a simulated scenario has on evoking creativity and empathy. And, for the given set of participants, gender did not show significant impact on the participants’ response.