Whitepaper - Predictive Maintenance
Predictive maintenance is becoming increasingly important, especially in machine and automotive production, which is characterised by Industry 4.0. Its methods are used to detect unusual behaviour patterns by comparing current sensor data with historical data. In this way, measures can be taken at an early stage to avoid a deterioration in product quality or even a failure of the machine. New predictive maintenance models also aim to uncover degenerative processes with the help of additional deeper diagnostics in order to predict the expected anomalous process behaviour.
Content of the white paper
The term predictive maintenance is clearly defined and sharply distinguished from the condition monitoring model.
We explain concepts such as machine learning or artificial intelligence (AI) and find possible business applications for predictive maintenance.
Find out how we structure our predictive maintenance projects and which resources, data and hardware and software infrastructure are required.
Our expert Senior Data Scientist Carlo Voß provides you with further insights into the methodology and models we use in our projects.
In relevant use cases from the automotive industry, you will find examples of how we have already successfully implemented predictive maintenance projects for our customers.
Your added values
Inspiration
Learn about possible applications of AI in the automotive sector and get ideas for your data project.
Practical examples
The white paper uses real use cases to show you the added value that AI is already delivering today.
Expertise
Benefit from our experience from over 1,000 data & AI projects - the majority of which are in the automotive sector.
Whitepaper - Predictive Maintenance
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