Reducing costs and downtime and increasing OEE
For organizations that use IoT-PREDICT, the business value of the solution—and the predictive maintenance it enables—is in less downtime, reduced costs, and improved OEE. Downtime on a production line can result in millions of dollars in lost revenue each year. By predicting and fixing problems before they occur, manufacturers can potentially minimize downtime, save money, and get more productivity from their factories in return for their existing capital.
Specifically, sensor and system data that IoT-PREDICT transforms into actionable insights helps manufacturers anticipate problems and resolve them more strategically and proactively. Those insights also give manufacturers critical information to help monitor and manage many other parts of their business, from reducing energy costs and consumption to trimming their maintenance overhead by taking the guesswork out of scheduled maintenance.
“Many manufacturers have huge data repositories, but no way to use the data effectively,” O’Connor says. “Moving the data to Azure with IoT-PREDICT helps them gain critical insights by applying Azure Machine Learning, Time Series Insights, Stream Analytics, and other Azure services that are baked into IoT-PREDICT.”