Abstract
Advancing digitalization is leading to new opportunities in maintenance. However, the implementation of data-driven solutions faces several challenges in industrial practice. Bridging the gap between research and practice, this paper proposes a procedural approach that covers the complete development and implementation process and enables industrial application of prescriptive maintenance. A multi-level model is developed to support the selection of the right type of data analytics application and appropriate analytics methods based on available data. Furthermore, a Data Canvas is introduced to provide an overview of relevant data sources. The proposed approach is demonstrated in the context of jewelry production.
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