Feasibility analysis for predictive maintenance

The possibility of analyzing spare parts requirements for vehicles in the field with a view toward optimizing warehousing. [at] designs, evaluates and implements a wide variety of use cases, always keeping the customer in focus.

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 between actual demand and the stock of spareparts for its vehicles in decentralized spare parts warehouses. A feasibility analysis is to be conducted to determine whether the spare parts demand can be predicted by using predictive maintenance,thereby optimizing warehousing.


Developing a data model of available data sources in close consultation with business experts. Incorporating external data sources such as weather- and landusage data, and interpolating them to map onto vehicle geo-locations.Developing simple PoC-based statistical models to predict part failures.


Awareness of the requirement for data sets and their availability for conducting data science projects has been achieved within the federal agency,and example results from the statistical models can be used to further advance the use caseinternally.

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