A Fuzzy-Network Analysis Approach for Modeling and Analyzing Team Dependencies in Product Development Projects

Abstract

Developing a complex product in a concurrent engineering environment requires managing information flow among ten or even hundreds of people of different specialties organized in a large number of product development (PD) teams. Managing these teams effectively requires understanding the level of information dependencies among them which are often vague and cannot be precisely predicted. Taking into account the limitations of relevant previous studies, this article proposes a fuzzy-social network analysis approach for modeling and analyzing the information flow among PD teams. The approach involves four major steps: mapping of dependencies, measuring the level of information dependencies based on the fuzzy set theory, visualizing the network, and performing quantitative analysis using three measures (network density, in-degree centrality, and out-degree centrality). To validate its practicality, the approach is used to model and analyze the dependencies among 22 PD teams in a real project adapted from the literature and involved developing an automobile engine. An advantage of the approach is that in addition to providing a holistic view of the interactions among PD teams, it permits PD project managers to identity the most important PD teams with respect to information flow control using a proposed new classification system that classifies PD teams under four categories: autonomous, receivers, transmitters, and transceivers.