By replacing components at fixed intervals.

By leveraging sensor fusion.

By upgrading firmware weekly to prevent any type of mechanical issue.

By continuously monitoring equipment conditions in real time and triggering alerts when needed.

By performing routine calendar-based maintenance checks.

By using machine learning algorithms trained on historical failure data.

By disconnecting equipment periodically to test for failures manually.

By using random sampling to estimate equipment status.