by Radicalbit 18 May 2020

The power of Machine Learning for Predictive Maintenance

Predictive maintenance for industry 4.0 helps determine the in-service equipment condition; this helps to estimate the correct time maintenance can perform. Its main goal is to prevent asset failure through production data analysis to spot repeated patterns. Moreover, it can predict issues before they might happen. Until now, factory managers and machine operators carried out preventive maintenance. The latter performs at regular intervals, but this is an ineffective activity that consumes unnecessary resources and drives productivity losses.

Thus, it’s not a surprise that it is quickly emerging as a number one Industry 4.0 use case for manufacturers and asset managers. The implementation of industrial IoT technologies to watch asset health, optimize maintenance schedules, and gain 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.