THE ANALYSIS AND MODELING OF THE ENGINEERING DESIGN PROCESS: FACTORS LEADING TO INNOVATIVE OUTCOMESOzaltin, Nur Ozge / NO (2013) THE ANALYSIS AND MODELING OF THE ENGINEERING DESIGN PROCESS: FACTORS LEADING TO INNOVATIVE OUTCOMES. Doctoral Dissertation, University of Pittsburgh. (Unpublished) This is the latest version of this item.
AbstractEngineering innovation is essential to solve many of the 21st century’s “grand challenges”, as it plays a strategic role in competitive environments. Currently, most design practices in engineering education focus on aspects of “good” technical design. However, to meet the competitive environment, elements of innovation must also be incorporated. This research has two overarching goals. The first is to determine the characteristics of teams and their design processes that lead to innovative artifacts. Regarding this, two research questions are explored. First, what attitudes and design activities do teams exhibit that are related to the innovativeness of their design artifact? Second, how do teams’ attitudes and their design activities traverse over the design process from problem definition to working prototype? To address these questions, two investigations that identify differences between innovative and non-innovative teams are performed. The first one, examining teams’ design activities, is a quantitative investigation addressing whether the engineering design process has any influence on the innovativeness of the artifact. Stepwise regression and association mining analyses are applied to determine the activities utilized, when they are utilized, and how teams navigate the process as depicted by their iterations. The second, examining teams’ attitudes about their progress, is a qualitative investigation that incorporates grounded theory and content analysis to examine the attitudes of teams and how this potentially affects the innovativeness of the artifact. The second goal of the research focuses on developing an intervention tool to increase the likelihood of innovative outcomes in design settings given engaged activities. This tool is formulized by a Bayesian network model. The results show that utilizing marketing activities in the early phase is essential; and design communication becomes critical in the late phase. Moreover, displaying a smooth iterative flow has a positive effect on the innovativeness of the artifact. This research also shows that the innovative teams act like problem solvers, as well as have the propensity to know what they do not know, and where to seek help. In close, the innovativeness of a design team is a function of both their chosen design activities and their attitudes. Share
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