Improvement of the Logistic Performance of Cluster-Oriented Decentralized Control in Material Flow Networks in Manufacturing

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Since several years, the control of operations in manufacturing and logistics moves from centralized planning towards decentralized control in real-time, enabled by 'intelligent objects'. Regarding decentralized control approaches, research has so far focused primarily on developing new control algorithms which provide a certain 'intelligence' to improve the achievement of logistic targets. Beside, there was a lot of effort to develop the required technologies to enable decentralized control, such as the Internet of Things or Industry 4.0. However, the underlying network structure of material flow systems and its influence on logistic performance has not been extensively studied, although the topology has to be considered along with algorithms and technology as a crucial success factor of decentralized control. For example, highly connected systems usually provide much more routing alternatives, while in turn the routing paths in sparsely connected systems have to be shared among much more objects. Both phenomena have a distinct impact on routing in material flow systems and therefore need to be considered during the design of control approaches for these systems. The goal of this project is the development of a network-based approach to divide a material flow system into clusters or modules, which are supposed to be governed by distinct types of decentralized control, in order to improve the achievement of logistic key figures.