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, you'll learn:
- The value opportunity of predictive maintenance
- Case studies of real-world examples with realized benefits
- Tactical approach to support predictive maintenance at scale
- Blueprint for getting started
Watch on demand today for immediate takeaways you can apply to your business.