Remaining Useful Life, failure probability, degradation index and time-to-maintenance can help convert condition data into planning information. They should be treated as estimates supported by evidence, not as guaranteed dates.
Establish trustworthy input
A prognostic model needs stable sensor installation, valid machine configuration and a representative baseline. Changes in duty, load, speed or maintenance state can alter the apparent degradation path and should be recorded with the trend.
Use several indicators together
Failure probability expresses likelihood, while degradation index describes progression and RUL estimates time remaining under assumed conditions. Baseline-active state, update count and aging factor help explain whether the model has enough history and how it is adapting.
Connect to maintenance decisions
- Use RUL bands to support inspection, spares and shutdown planning.
- Require corroborating vibration, temperature or process evidence before major intervention.
- Escalate rapidly when condition severity changes faster than the expected degradation path.
- Review model performance after maintenance and reset or rebuild the baseline where appropriate.
Prognostic outputs are firmware- and model-dependent. Confirm the applicable firmware profile, register-map revision and commissioning procedure before relying on them operationally.
Technical basis: PyXis Smart 3-Axis Vibration Sensor datasheet TTN-DS-2026-002, issued 19 July 2026. Confirm the current hardware, firmware and controlled document revision before implementation.
