Information Flow Through Stages of Complex Engineering Design Projects: A Dynamic Network Analysis Approach


The pattern of data flow through the network of interdependent design activities is considered an necessary determinant of engineering design process results. A previously unexplored aspect of such patterns relates to the temporal dynamics of knowledge transfer between activities as those activities are implemented through the network of people executing the project. To deal with this gap, we develop a dynamic modeling technique that integrates both the network of people and also the network of activities in the project. We then use a massive dataset collected from an industrial setting, consisting of project-connected e-mails and activity records from the design and development of a renewable energy plant over the course of additional than three years. Using network metrics for centrality and clustering, we have a tendency to make 3 vital contributions: one) We tend to demonstrate a completely unique method for analyzing data flows between activities in complicated engineering design projects; two) we tend to show how the network of data flows in a giant-scale engineering project evolved over time and how network analysis yields several managerial insights; and three) we tend to offer a useful new representation of the engineering style process and thus support theory-building toward the evolution of information flows through systems engineering stages. Implications embody steerage on how to research and predict data flows along with higher planning of knowledge flows in engineering style projects consistent with their individual stage and activity characteristics.

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