Increasing the efficiency of machines and plants requires powerful, multifunctional solutions that provide data on the machine condition in addition to the machine control. With the condition monitoring information obtained from this the performance of each machine and thus of the entire plant can be optimized
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Time-to-event (TTE) use-cases crop up in many places across industries. Some examples would be: the prediction of customer churn (the sales domain), remaining-useful-life or time-to-failure TTF (predictive maintenance), or anomaly detection (machine monitoring). Some events are difficult to predict as they are hidden. We can instead try to look for interim events to improve prediction accuracy.
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Time-to-event (TTE) use-cases crop up in many places across industries. Some examples would be: the prediction of customer churn (the sales domain), remaining-useful-life or time-to-failure TTF (predictive maintenance), or anomaly detection (machine monitoring).Some events are difficult to predict as they are hidden. We can instead try to look for interim events to improve prediction accuracy.
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Unscheduled downtimes in production due to worn out or unserviced molds in machines can cause high costs and are a well-known problem for a lot of companies. In order to prevent these issues and optimize the use of their injection molds, a Swiss chocolate mold producer installed a predictive maintenance system via industrial RFID technology.
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White paper: Mold Management with RFID for Injection Molding – A Step to Industry 4.0 The terms Industry 4.0, Big Data and the Industrial Internet of Things (IIoT) are now on everyone’s lips. They describe the intelligent networking of extremely diverse areas in industry. Objective of this White Paper
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