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Design problem decomposition: an empirical study of small teams of facility designers

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Abstract

Decomposing complex design problems is an important component of design processes. When a design problem is too complex to solve all at once, the problem is decomposed into manageable subproblems. Previous work on design processes has identified some general decomposition patterns and has studied how individual designers decompose design problems; this study examines the way variables are grouped into subproblems, the process of decomposition, and whether small teams use similar decomposition patterns. Data were collected from five teams as they solved a facility design problem, and the subproblems that they considered were analyzed and compared. Using a mix of qualitative and quantitative analysis techniques, we examined (1) whether their subproblems group tightly coupled design variables (and separate weakly coupled variables); (2) whether their decompositions (subproblems and the sequence in which they were solved) follow a top–down design process; and (3) whether different teams used the same decompositions. Our results suggest that teams followed a partial top–down design process that moved from breadth- to depth-first search, and that subproblems were often driven by two types of coupling among design variables. However, the inconsistency of observed approaches suggests that there is room for improvement in how human designers decompose problems. By identifying these issues, the results lay a foundation for future research to provide better support for human designers in decomposing problems.

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Data availability

The observations of human designers cannot be shared to protect the confidentiality of the research subjects. However, the coded data generated and analyzed in this study are fully described in Figs.  4, 5, 6, 7 and 8 and Table 8. The data are available in MS Excel or comma-separated value formats from the first author upon request.

Notes

  1. Specifically, for a TS to correspond to a RS, a TS had to have two to four of the variables in three to five variable RSs, depending on the size of the RS. For a TS to be a subset of a RS, it had to have two to six of the variables in the RS. A TS is related to no RS if it had at most one variable from any RS or if it corresponded to multiple RSs.

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Acknowledgements

The authors acknowledge the assistance of Connor Tobias and Azrah Azhar Anparasan, who assisted with the data collection and analysis methods. This research was supported by National Science Foundation Grants CMMI-1435074 and CMMI-1435449

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Authors and Affiliations

  1. George Washington University, Washington, DC, USA

    Erica L. Gralla

  2. University of Maryland, College Park, MD, USA

    Jeffrey W. Herrmann & Michael Morency

Authors
  1. Erica L. Gralla
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  2. Jeffrey W. Herrmann
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  3. Michael Morency
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Correspondence to Erica L. Gralla.

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The research on human subjects described in this paper was conducted in compliance with ethical standards, with the approval of the Institutional Review Boards of the University of Maryland and the George Washington University.

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Appendix

Appendix

Figures 4, 5, 6, 7, and 8 show the timelines for all teams, including which variables were worked on at which times, and their clustering into subproblems. Table 8 describes all the subproblems found for each team, including which variables are included in each subproblem, a label and a description for each.

Fig. 4
figure 4

Timeline for Team 1

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Fig. 5
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Timeline for Team 2

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Fig. 6
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Timeline for Team 3

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Fig. 7
figure 7

Timeline for Team 4

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Fig. 8
figure 8

Timeline for Team 5

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Table 8 Subproblems for each of the five teams
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Gralla, E.L., Herrmann, J.W. & Morency, M. Design problem decomposition: an empirical study of small teams of facility designers. Res Eng Design 30, 161–185 (2019). https://doi.org/10.1007/s00163-018-0300-0

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  • DOI: https://doi.org/10.1007/s00163-018-0300-0

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