
Study
Machine Learning in Maintenance

What did we analyse in our study?
- What potential do companies see through the use of machine learning in maintenance
- How widespread is the use already
A brief overview
AI is only now becoming practically relevant, thanks to more powerful computers and large amounts of data. Political strategies such as ‘Digital Switzerland’ (2018) and Germany's AI strategy with 3 billion euros in funding show the momentum. A BMWi study (2020) found that AI-supported innovations generated a turnover of 11 billion euros in Germany in 2018.Nevertheless, the use of AI in the DACH region remains limited and there is often a lack of clear differentiation from machine learning (ML). There is potential in maintenance in particular: over 75% of companies are familiar with ML, but 44% are not planning to use it. All results follow in detail.
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Our expert

Ewald Rehm Partner & Managing Director
is a leading expert in asset lifecycle management with SAP and optimises company processes across the entire asset lifecycle - for greater efficiency and sustainability.
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