This whitepaper explores various methods of leveraging predictive maintenance to optimize your connected plant.
Plant maintenance is like flossing. Everyone knows they should do it, but it’s easy to deprioritize when there aren’t any visible problems. Just like neglecting oral health can be costly in the long run, failing to do preventative plant maintenance can increase operating costs and the risk of unplanned shutdowns — translating to millions of dollars in lost revenue. Downtime costs the average plant between 5 and 20 percent of its overall productive capacity. Unplanned downtime caused by equipment failure costs industrial manufacturers $21 billion every year. A great way to unlock new revenue streams can be done by leveraging predictive maintenance.
For years maintenance professionals have combined quantitative and qualitative approaches to try to predict failures
and mitigate downtime in their manufacturing facilities with limited success. New industrial internet of things (IIoT) tools improve on these methods using machine learning to take a more data-driven approach.
Converting to a predictive maintenance posture opens the door to optimize maintenance tasks in real-time and maximize the useful life of equipment while avoiding disruption to operations. Inside of this Very white paper, it breaks down the different types of maintenance and the ROI you can expect to see from leveraging predictive maintenance, in particular.