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Abstract This paper investigates how the core technical processes of the INCOSE model of systems engineering differ from other models of designing used in the domains of mechanical engineering, software engineering and service design. The study is based on fine-grained datasets produced using mappings of the different models onto the function-behaviour-structure (FBS) ontology. By representing every model uniformly, the same statistical analyses can be carried out independently of the domain of the model. Results of correspondence analysis, cumulative occurrence analysis and Markov model analysis show that the INCOSE model differs from the other models in its increased emphasis on requirements and on behaviours derived from structure, in the uniqueness of its verification and validation phases, and in some patterns related to the temporal development and frequency distributions of FBS design issues. 

Abstract Professionals need to collaborate with multiple stakeholders in product development to stay competitive and to innovate. Through their values and mission, companies develop a specific working environment that can lead to the development of design methods and tools. In this article, we study design team dynamics of professional engineers working in two different organizations. We aim at identifying differences in team behaviors between teams drawn from two different organizations. The goal is twofold. At a theoretical level, we aim at gaining a better understanding of the effect of work culture on design team behaviors. At a methodological level, we explore whether grouping teams from different organizations into a single larger sample to obtain better reliability is relevant. To do this, we compared two cohorts of teams based on which company engineers worked at. Both companies are international organizations employing more than 50,000 collaborators worldwide. Teams of three engineers worked on designing a next-generation personal assistant and entertainment system for the year 2025. We analyzed each team’s design interactions and behaviors using quantitative tools (Multiple Factor Analysis and Correspondence Analysis). Results from this exploratory analysis highlight different behaviors between cohorts as well as a common overall approach to team design thinking. 

Abstract Designers faced with complex design problems use decomposition strategies to tackle manageable sub-problems. Recomposition strategies aims at synthesizing sub-solutions into a unique design proposal. Design theory describes the design process as a combination of decomposition and recomposition strategies. In this paper, we explore dynamic patterns of decomposition and recomposition strategies of design teams. Data were collected from 9 teams of professional engineers. Using protocol analysis, we examined the dominance of decomposition and recomposition strategies over time and the correlations between each strategy and design processes such as analysis, synthesis, evaluation. We expected decomposition strategies to peak early in the design process and decay overtime. Instead, teams maintain decomposition and recomposition strategies consistently during the design process. We observed fast iteration of both strategies over a one hour-long design session. The research presented provides an empirical foundation to model the behaviour of professional engineering teams, and first insights to refine theoretical understanding of the use decomposition and recomposition strategies in design practice. 

This article introduces and applies a methodology to analyze the effect of team diversity on team design cognition. We explore team diversity in relation to team members’ gender. We studied two types of teams: heterogeneous teams composed of one female and one male mechanical engineering student and homogeneous teams of two male mechanical engineering students. We analyzed 28 design protocols using the Function-Behavior-Structure ontology to code protocols and measure team cognitive design behavior. We found that male design students in the mixed teams tend to dominate the design activity. Also, we found that mixed teams 

This article introduces and applies a methodology to analyze the effect of team diversity on team design cognition. We explore team diversity in relation to team members’ gender. We studied two types of teams: heterogeneous teams composed of one female and one male mechanical engineering student and homogeneous teams of two male mechanical engineering students. We analyzed 28 design protocols using the Function-Behavior-Structure ontology to code protocols and measure team cognitive design behavior. We found that male design students in the mixed teams tend to dominate the design activity. Also, we found that mixed teams showed significantly more co-design activity compared to male only teams.