RRAMAC has been providing predictive maintenance solutions for over a decade, covering a broad range of industries and applications. There are three basic techniques for implementing predictive maintenance including condition monitoring, machine learning and simulation. The Simulation approach to predictive maintenance leverages human knowledge of cause and effect relationships which apply to the specific machine or application. These relationships are applied to simulation software which then predicts failures based on the model and uses an application specific machine learning algorithm to fine tune the predictions.
The simulation approach is the IoT solution RRAMAC uses. The simulation model produces much faster results and requires fewer sensors and smaller data storage requirements resulting in a much more compelling return on investment than machine learning alone.
Predictive Maintenance Solution Case Studies
We selected three case studies that display how the simulation predictive maintenance model can impact your business. Predictive maintenance has been used in the water / wastewater, automotive manufacturing, and even generating compressed air as a service. Download the brochure to read the three case studies today. RRAMAC provides IoT solutions from simple equipment monitoring to prescriptive and predictive maintenance and more. Contact us today to tell us about your project.
