Nowadays material flow in factories is realized by different concepts of transport. Each of those specific conveyers has pros and cons due to its concept. In general, the state of art of transport systems have a low flexibility of the path planning and are not suitable for dynamic transport requirements, wherefore they are designed for a specific application. Generally, the common systems cover a specific task of transportation and can fulfill a predefined maximum amount of transportation orders. Due to the effects of mass-customization there is an increase of the variance of the products combined with a reduction of the number of units per variation and a volatile costumer demand. Therefore, it is necessary that the next generations of production lines, especially the intralogistics transportation systems, have to be designed more adaptable and flexible. The object of the research in this paper is a cyber-physical material flow system with flexible, autonomous and collaborative vehicles combined with centralized sensors to digitalize the workspace. Furthermore, the number of vehicles in the system can be adjusted to the volume of the transport requirement, wherefore the system is suitable for different tasks in the intralogistics. Due to the approach of a decentralized digitalization of the workspace on the one hand side and the decentralized architecture of the path planning and order allocation system on the other hand side the concept lead to a nearly endless scalability of the system. The scalability is only restricted by the maximum number of entities which can use the communication system. Therefore, it is possible that the system adjust itself to the actual intralogistics demand as well as the dimension of the field of operation. This lead to a self-adjustable intralogistics transportation system which avoid a physical redesign of the whole system if the intralogistics demand is changing. To validate the approach, the decentralized intelligence of the transport entities and the production units is implemented in a discrete event simulation. In this simulation environment different task allocation methods, sizes of the transportation fleet, lot size management concepts and site layout concepts can be compared and rated which each other.
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