Feasibility analysis on predictive maintenance

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 centres.store. 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 internally.drive.

Are you interested in your own use cases?

Our Case Studies

- Get even more detailed insights into our customer projects -

Smart cooking with Thermomix

Smart cooking with the Thermomix

Case Study AI at Munich Re

Data Operations at Munich Re


Data & AI Knowledge

Creating added value from data & AI together


Discover professional articles on Data & AI as well as the latest industry news.


Dive into our Best Practices and Industry Exchanges. Discover new dates and recordings of past webinars.


Learn more about the use of Data & AI in your industry with our white papers, case studies and research.