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This survey systematically assesses and classifies the state-of-the-art algorithms applied to data-driven maintenance in recent literature. The taxonomy provides a so far not existing overview and decision aid for research and practice regarding suitable AI approaches for each maintenance application. Moreover, we consider trends and further research demand in this area. 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