I have written the following post about Predictive Maintenance and flexdashboard at my company codecentric’s blog:
Predictive Maintenance is an increasingly popular strategy associated with Industry 4.0; it uses advanced analytics and machine learning to optimize machine costs and output (see Google Trends plot below). A common use-case for Predictive Maintenance is to proactively monitor machines, so as to predict when a check-up is needed to reduce failure and maximize performance. In contrast to traditional maintenance, where each machine has to undergo regular routine check-ups, Predictive Maintenance can save costs and reduce downtime. A machine learning approach to such a problem would be to analyze machine failure over time to train a supervised classification model that predicts failure. Data from sensors and weather information is often used as features in modeling.
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With flexdashboard RStudio provides a great way to create interactive dashboards with R. It is an easy and very fast way to present analyses or create story maps. Here, I have used it to demonstrate different analysis techniques for Predictive Maintenance. It uses Shiny run-time to create interactive content.
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Continue reading at https://blog.codecentric.de/en/2017/11/explore-predictive-maintenance-flexdashboard/
