ResearchFields of Research
Structural Planning

Structural Planning

The purpose of structural planning is to carry out a complete planning activity for the long-term design of an infrastructure, covering all effective systems and functional areas. It serves as decision support for the type, quantity and spatial arrangement of influencing factors and work systems. This includes, among other things, the sub-areas of infrastructure planning and material flow and layout planning.


PLANNING INDUCTIVE CHARGING INFRASTRUCTURES ON AIRPORT APRONS

Schematic representation of a loading process

The objective of planning inductive charging infrastructures on airport aprons is to develop an infrastructure that ensures uninterrupted service operations of electrically operated apron vehicles. This infrastructure can be implemented in various ways, differentiating between stationary and dynamic charge transfer. Both stationary and dynamic inductive charging systems enable charge transfer between the road infrastructure and the vehicle to be charged independently of the user. In addition, the dynamic inductive charge transfer enables charging of vehicles while driving. As part of an optimization process, the components required for such an inductive charging system are arranged on the apron at minimum cost, taking vehicle consumption into account.


MODELING AND PREDICTING THE THROUGHPUT OF STOCHASTIC FLOW LINES WITH LIMITED LOCAL BUFFER CAPACITY VIA ARTIFICIAL NEURAL NETWORKS

Exemplary structure of the artificial neural network for the analysis of flow production systems

Flow production systems are often used to organize the production of large quantities of homogeneous goods. In flow production systems, different tasks are performed on the workpieces at serially arranged stations. In case of stochastic influences on the processing times at the stations, blocking or starving of parts of the system may be a common occurrence. Thus, to sustain the material flow, expensive buffers are set up between the stations. To find an efficient structure of the flow line, which minimises the costs while generating maximum throughput, fast evaluation procedures are needed. In this approach, we use artificial neural networks to predict the throughput of the overall system.