Utilizing cluster analysis to structure concurrent engineering teams

Abstract

The problem of structuring a concurrent engineering team was studied. This research considered various mathematical clustering approaches to group product development design tasks together, and then constructed cross-functional teams based on the task clusters formed from each approach, Resultant team structures were evaluated against each other, and against a traditional discipline-centered hierarchical structure. The goal of this effort was to develop a structuring methodology for concurrent engineering teams that would allow projects to be completed faster, and with a lower risk of project failure. Team structures were developed using alternative clustering techniques and different combinations of data as inputs into the clustering techniques. Clustering approaches included single linkage, complete linkage, average linkage, the centroid method, and Ward's method. Data sources were from the initial stages of product development, and included task risk levels, task precedence relationships, disciplines required, personnel available, task technical importance, task difficulty, task priority, component requirement interactions, and projected communication levels between design tasks. Additional analysis was done on the effects of multiteam assignments for critical personnel. Team structures developed using the average linkage clustering approach and a data set composed of projected communication levels between tasks and discipline requirements for each design task were found to support the development of shorter duration projects with lower risk levels.

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