Role of Representation in Subsystem Clustering: Effects of Distance Between Elements

Abstract

Engineering systems are often represented in terms of their function or the constituent components. Several representation styles and modalities have been proposed and used in the engineering design literature. This study investigates the effects of three different system representation styles on system understanding. Component graph, function graph, and function structure are compared in term of subsystem clustering. A mixed replication experiment is conducted where undergraduate student participants are asked to group or cluster system elements into subsystems. Data collected is analyzed in terms of distances between elements and occurrence of element pairs in the same parent cluster. Distances are measured in terms of connectivity, physical distance, and semantic distance. Results show that participants tend to cluster elements together when they are separated by smaller distances. Connective and physical distances show clear trends with pair occurrence, whereas trends with semantic distance are unclear. Correlations between physical distance and pair occurrence point to differences between the representation styles. Alternatively, deviations from the general trends indicate that strength of influence for each of the distance measures may be contextually dependent. Findings suggest that visual layout of system elements affects system understanding, and we should be cognizant of the implicit information that we may be communicating by our choice of layout. Finally, limitations of the research are discussed, and future work is identified.

The Influence of Representation on System Interpretation: A Search for Most Common Set Partitions

“…This strategy allowed for the potential discovery of partitions that best match the observed partition set without assuming that the most likely partition had to be within the set of observed participant partitions. All three analysis methods showed differences in clustering behaviour based on representation modality, which extends the authors' prior work (Murphy et al, 2022;Patel et al, 2022) and partially addresses the first research question. A deeper analysis that investigates specific factors that lead to differences in clustering behavior is left to future work.…”

“…Initially, this method appears to give a coherent result. For the hair dryer component graph show in Figure 2 (left), each element of this partition is within exactly one cluster as expected and the clusters include elements that are spatially adjacent to each other (see (Patel et al, 2022)). In other cases, partitions generated using this method contained elements that belonged to multiple clusters.…”

“…For additional details and discussion about the study design, please refer to prior work on this topic (Murphy et al, 2022;Patel et al, 2022). The specific methods explored to find a most likely partition that represents the observed data set are described in Section 4 for organizational clarity.…”

“…The three constructed packets were distributed to the participants randomly. For a complete description of the design task and prompt, see (Murphy et al, 2022;Patel et al, 2022).This paper reports on results from this research study with a total sample size of n = 72. Since the participants were divided into three groups randomly, sample sizes for each product-representation pair range from 21 to 27.…”

“…Functional decomposition in engineering design is described followed by an overview of mathematical concepts foundational to the analysis presented in this paper. The research presented in this paper builds from prior work (Murphy et al, 2022;Patel et al, 2022).…”