@article{Beber2014TowardsUnderstandingRelation,
Author = {Moritz E. Beber and Till Becker},
Title = {Towards an Understanding of the Relation between Topological Characteristics and Dynamic Behavior in Manufacturing Networks},
Journal = {Procedia CIRP},
Year = {2014},
Volume = {19},
Number = {0},
Pages = {21-26},
Note = {2nd CIRP Robust Manufacturing Conference (RoMac 2014)},
Doi = {http://dx.doi.org/10.1016/j.procir.2014.05.005},
Url = {http://www.sciencedirect.com/science/article/pii/S2212827114006337},
Keywords = {manufacturing systems},
Abstract = {Abstract Manufacturing systems can be modeled as networked work systems connected by material flow. Characteristics such as performance and robustness are influenced by the manufacturing network's static structure, i.e. the topology, and its dynamic behavior, i.e. the material flow. The statistical analysis of the topological features of networks has been used in many disciplines to predict dynamic behavior, however, the meaningfulness of each individual topological measure can differ between network types. Therefore, it is necessary to determine which topological measures can be used to evaluate and compare manufacturing networks. This article investigates procedures to identify significant over- or underrepresentation of three-node subgraphs, known as motifs, and the dynamical importance of single nodes in terms of their effect on the largest eigenvalue. The results show that both approaches are suited to indicate dynamical behavior of a manufacturing systems solely based topological information. These techniques can be used for a quick assessment of existing or planned manufacturing systems without extensive and complex modeling.}
}
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