Sanwald, Paul Jakob Julius

Diploma Thesis:
2016

Topic:
Construction machinery-related data and their use in the planning and construction process

Editor:
Paul Jakob Julius Sanwald

University Professor Responsible:
Univ.-Prof. Dr.-Ing. Dipl.-Wirt.-Ing. Jens Otto

Supervisor:
University Supervisor:    Dipl.-Ing. Janik Mischke

Editing Period:
26.11.2024 until 29.04.2025

Abstract:
The digitalisation of the construction and construction machinery industry poses considerable challenges for those involved. The introduction of digital processes in companies generates extensive data and valuable information that offers significant potential for individual companies and the construction industry as a whole. The focus here is on the digital image of a construction machine's activities in the form of data. In particular, the use of machine-related data can generate concrete added value, for example by optimising construction process planning, deriving key figures for performance evaluation or improving work processes. However, this requires uniform standards in terms of data quality, data security and data exchange, which have not yet been sufficiently established. Analysing data from four widely used construction machines in building construction and incorporating the MiC 4.0 results made it possible to define seven practical use cases. It became clear that structured data collection and the use of open, manufacturer-independent platforms are necessary in order to fully utilise the existing potential. Artificial intelligence and machine learning also offer the possibility of efficiently evaluating large volumes of data and making a targeted contribution to process optimisation. The results of the study make it clear that the targeted and standardised use of machine data not only leads to increased efficiency, but can also pave the way for the sustainable and networked construction site of the future.