Over the years, our industries have made efforts collect equipment data. Through this effort, we now have significant amounts of data available to detect equipment problems. However, it is necessary to sort through this data to determine which equipment requires attention. Coupling predictive analytics and collaboration with the data available allows maintenance organizations to focus on the equipment that needs repair.
This discussion will review two case studies, and how predictive analytics provides early warning of failure. The early warning enables maintenance organizations to work through the process of detection, diagnosis, communication, and action to prevent costly failures.