Predictive maintenance is an area receiving significant attention because of the operational efficiency it can provide. IoT and Industrial IoT (IIoT) are improving access to field data, key to predictive maintenance. Considerable effort is being expended using traditional analytics and reporting tools to help equipment operators be more productive. As more sensors are added and data access improves, advances in machine learning are improving equipment condition predictions, enabling more efficient operation.
Tom Gill, an Executive Consultant at CIMdata, shares his thoughts on this topic and more in a recent blog posting which is available at https://www.cimdata.com/en/resources/cimdata-blog/item/11550-predictive-maintenance-benefits-of-closing-the-product-lifecycle-loop
CIMdata will look into this topic in more detail at the upcoming PLM Market & Industry Forum events which will take place in Ann Arbor MI; Frankfurt Germany; Pune, India; Beijing, China; and Tokyo, Japan this coming April. The theme for 2019 is "Augmented Intelligence: Applications Across the Product Lifecycle.”
For more information visit our PLM Market & Industry Forum web pages at http://www.cimdata.com/en/education/plm-market-industry-forums
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