Development of a predictive maintenance use case for a federal authority

The possibility of meeting spare parts requirements for vehicles in the field is to be analysed with regard to Optimisation of warehousing.

Evaluation of the available data basis with regard to predictive maintenance projects

Recommendations regarding data availability to successfully implement predictive maintenance projects


A federal agency experiences a large discrepancy betweenbetween actual demand and the stock of spare parts.for their vehicles in decentralised spare parts A feasibility analysis is to be carried out to find out whether the need for spare parts through the use of predictive Maintenance predicted and stockpiling thereby can be optimised.


Development of a data model of the available datasources in close consultation with experts.Integration of external data sources such as weather and landdata, and interpolation of this data in order to apply it to the The system is also capable of transmitting the geo-positions of the vehicles.Development of simple statistical models on a PoC basis, to predict parts failures.


In the federal agency, awareness was raised for the Requirement for data files and their availability achieved for the implementation of data science projects.Exemplary results of the statistical models can be be used to further advance the use case

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An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.


There will be a interactive and Flexible application, including of different maps with two different views implemented.


Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.

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