DocumentCode :
1347065
Title :
Utilizing cluster analysis to structure concurrent engineering teams
Author :
Componation, Paul J. ; Byrd, Jack, Jr.
Author_Institution :
Dept. of Ind. & Syst. Eng., Alabama Univ., Huntsville, AL, USA
Volume :
47
Issue :
2
fYear :
2000
fDate :
5/1/2000 12:00:00 AM
Firstpage :
269
Lastpage :
280
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
Keywords :
concurrent engineering; pattern recognition; personnel; product development; project management; risk management; Ward´s method; average linkage; average linkage clustering approach; centroid method; cluster analysis; complete linkage; component requirement interactions; concurrent engineering teams; concurrent engineering teams structure; critical personnel; cross-functional teams; data set; discipline-centered hierarchical structure; disciplines required; mathematical clustering approaches; multiteam assignments; personnel available; product development; product development design tasks; project failure; projected communication levels; shorter duration projects; single linkage; task clusters; task difficulty; task precedence relationships; task priority; task risk levels; task technical importance; team structures; team structures development; Concurrent engineering; Couplings; Design engineering; Lifting equipment; Personnel; Product design; Product development; Quality function deployment; Systems engineering and theory; Team working;
fLanguage :
English
Journal_Title :
Engineering Management, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9391
Type :
jour
DOI :
10.1109/17.846793
Filename :
846793
Link To Document :
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