KI-Methoden zur Planung und Datenauswertung in der Baulogistik
AI methods for planning and data analytics in construction logistics
Bachelor thesis, Master thesis
From Machine Learning in logistics process control to Natural Language Processing for the evaluation of delivery notes: Construction logistics is a decisive factor for the successful implementation of a construction project. In the stationary industry, detailed planning of logistics has long since become standard. The characteristics of the construction industry make such detailed, but also complex planning difficult. The use of artificially intelligent systems can significantly reduce the effort involved in logistics planning, simplify its use in practice and increase the efficiency of construction logistics.
Construction logistics deals with the transport and storage of construction materials as part of the execution of a construction project. In addition to the material flows, i.e. the actual transport of the building material, the focus is also on the information flows that announce and accompany a delivery. Under the influence of the digitalisation of the construction industry, rising costs and the shortage of skilled workers in the construction industry, possibilities are increasingly being sought to make the handling of a construction project and thus also the handling of construction site logistics more efficient using digital tools. Artificially intelligent algorithms can be used for the more precise calculation of demand forecasts, the optimisation of storage areas and transport routes on the construction site as well as for the evaluation of information flows, for example through the automated linking of delivery notes and invoices with the Building Information Model (BIM). In a possible final thesis, one or more AI methods should therefore be selected and their potential for optimising construction logistics investigated.
Note: The content in this area covers a range of final theses. For concrete topics / tasks, your own suggestions and ideas can be submitted.
Supervisor
Maximilian Gehring, M.Sc.
Prerequisites
Interest in the implementation of AI algorithms. Knowledge in this area is an advantage, but not necessarily required.
Start
As of now
