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Avoiding downtime is one of the major concerns of manufacturing industries. In the era of connected industry, acquiring data has become cheaper than ever; however, turning that data into actionable insights for operators is not always straightforward. In this work, we present a manufacturing scenario involving a circular blade rubber cutting machine, where the goal is to minimize downtime. Historical cutting data are available, and the aim is to provide the machine operators with an intuitive tool that helps them reduce this downtime. This work demonstrates how, in an Industry 4.0 environment, data can be leveraged to minimize downtime. To achieve this, different survival model approaches are compared, a Health Index (HI) is developed, and the model deployment is analysed, highlighting the importance of understanding the model as a dynamic system in which the operator plays a key role.
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Belloso et al. (2024) studied this question.
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