The power of Machine Learning for Predictive Maintenance
Predictive maintenance for industry 4.0 helps determine the condition of in-service equipment in order to estimate when maintenance should be performed. Its main goal is to prevent asset failure by analyzing production data to spot patterns and predict issues before they happen. Until now, factory managers and machine operators carried out preventive maintenance, scheduling it at regular intervals, but this is an ineffective activity that consumes unnecessary resources and drives productivity losses.
Thus, it’s not a surprise that predictive maintenance is quickly emerging as a number one Industry 4.0 use case for manufacturers and asset managers. Implementing industrial IoT technologies to watch asset health, optimize maintenance schedules, and gaining real-time alerts to operational risks, allows manufacturers to lower service costs, maximize uptime, and improve production throughput.
Our high-value use case shows how to quickly and successfully implement Predictive Maintenance within your organization