Autor: Florian Harjes

In general, rental articles circulate in closed logistic systems, where the order parameters determine the material flow. As the planning horizon often comprises several subsequent orders at different locations, the corresponding transport and route planning is a complex task. Additionally, dynamic effects, such as thefts, damages, rush orders as well as new orders or order changes complicate the proceeding. This paper introduces the concept of an autonomously controlled route planning for rental articles that bases on the Distributed Logistics Routing Protocol (DLRP). At this, an example from the field of event logistics illustrates the concept.

The disposition and control of orders in the field of event logistics constitutes a complex and dynamic challenge. Changing venues, temporal restrictions as well as order changes and high customer demands require a flexible planning of the related logistic processes. Methods from the field of autonomous control offer a promising approach to cope with these problems. This contribution deals with the design of a special module for the information acquisition within the related logistic processes, as the provision of actual planning data is an indispensable prerequisite for the application of autonomous control.

Dynamics and complexity of today`s production systems bring established approaches for production planning and control to their limits. Accordingly, developing new concepts and methods is a key point for research in this area. The combination of a decentralized control structure and innovative methods from the field of artificial intelligence seems promising here. Open source tools have proven their applicability to implement those methods. They are disposable and can be flexibly adapted to many problems. This contribution introduces an approach for the decentralized control of a shop floor. Here, artificial neuronal networks are used as adaptive control instruments. The simulation of these networks is performed with the open source tool Stuttgart Neural Network Simulator (SNNS) and its successor Java Neural Network Simulator (JNNS).

Today`s complex and dynamic logistic processes are largely addicted to the efficient management of relevant information. Integrated into centralised planning and control structures, the flow and management of information is mostly handled in separate processes or sub processes. This proceeding results in an additional effort for the information processing and in corresponding delays during the process execution. This is especially the case for mobile work processes. Wearable computing systems offer the possibility to use modern information and communication technologies for a direct integration of the information processing and information management into the mobile work process. In this way the mobile user is discharged and able to concentrate on his logistical main task.

Advancements in the automation of technical systems enable the simultaneous accomplishment of multiple complex functions. Through further integration of information and communication technologies, systems will be able to communicate among each other and autonomously adapt their behaviour to changes in the environment. For the realisation of logistic functions, autonomous robots are promising systems. For the development and prototypal testing of such robots the automobile terminal was chosen due to its specific attributes and challenges. This article introduces an approach for the combination of security services and continuous inventory by means of autonomous and cooperating robots. To enhance the efficiency of automobile terminals, innovative information and communication technologies are implemented and robust autonomous robots developed.