The Future for Variable Frequency Drive Predictive Maintenance

Predictive maintenance continues to evolve using applied analytics to solve problems in manufacturing industries. Whether it's built into an end device, operating in the central control system, or deployed across an enterprise on various levels, analytics solutions can solve some of the toughest challenges. The scalability of an analytics solution can optimize the speed at which information is consolidated and presented to a user so they can optimize system performance. While these predictive maintenance features already exist in the drive, there is always a desire to know the status of this critical information at the right time by the right person to ensure the value of predictive maintenance is realized. Predictive models on top of artificial intelligence (AI) techniques will be the key to reliable drives operation in future. With a common framework for all components and consistent plantwide integration, systems will be designed with predictive models that can learn and adapt to actual drive usage patterns and predict remaining useful life (RUL) of the components. Goal today is the same as tomorrow - minimizing unplanned downtime and reducing unexpected losses.