Having the plant’s equipment undergo unplanned maintenance is one of any manager’s worst nightmares. Add tight deadlines to this equation, and the resulting outcome will be even more worrisome. Unplanned stops are usually a considerable waste of both time and money. The Predictive Maintenance techniques, an approach that allows anticipating equipment failure before it takes place, were developed to avert this dreadful scenario. Furthermore, with a continuous data analysis, errors in operation and configuration can easily be detected before they cause any major consequences, and then acknowledged and fixed.
When Predictive Maintenance is used as an upkeep strategy for the plant, maintenance is only performed when necessary, and before any failure takes place. This type of strategy generates many benefits, such as: less time is wasted in equipment under maintenance and, consequently, in production stops due to faulty devices; less money is spent on parts and supplies; etc.
An important asset for the predictive maintenance program is data management. Therefore, it will require using technologies to continuously collect, process, put together, structure, and analyze large chunks of data, mixing factory floor data with corporate information from MES systems, Maintenance Management, and ERP, for example.
In order to help make Predictive Maintenance a reality for companies of all sizes, Elipse Software provides software tools for all the implementation stages of this methodology, from collecting and storing data efficiently to simulating, continuously analyzing, and visualizing the results.
Elipse Software’s solution allows executing commands quickly, with no need for skilled labor, while tracing all productive processes at AVM’s automation engines plant