Kalypso acquired by Rockwell Automation, Inc. (NYSE: ROK). Read the press release.
In an Autonomous Enterprise, real-time sensory information is combined with advanced machine learning algorithms to help equipment maintenance staff predict failures, reduce downtime and improve worker safety.
However, predicting equipment failures is only one piece of the puzzle. Companies that pair enterprise systems and CMMS (Computerized Maintenance Management Systems) with asset performance management data can minimize downtime and production losses while improving the quality of goods. By automating important yet labor intensive tasks like scheduling work orders, forecasting, and ordering new parts, manufacturers achieve greater efficiency and higher output by reducing human error.
In this session, we will showcase leading practices to support predictive maintenance at scale and highlight the advantages of today’s modern factories. We will also provide a blueprint for getting started with predictive maintenance – progressing from data collection to predictive and prescriptive modeling – all in the context of use cases from industrial manufacturers.
During this exclusive, invitation-only event, you'll learn:
Don’t miss an opportunity to hear the latest technologies and methodologies based on leading use cases in the industrial manufacturing industry. Leverage this opportunity to learn immediate takeaways you can apply to your business.