AdvancedTopic 102 of 102Manufacturing, Robotics & Systems

Prognostics and health management

Predicts remaining useful life from condition data.

In depth

PHM uses sensor data and models to detect anomalies, diagnose faults, and predict remaining useful life (RUL) to schedule maintenance just in time. Approaches: physics-based, data-driven (ML), hybrid; features from vibration, temperature, current. Needs data quality, failure data and decision logic; reduces downtime and cost.

Key points

  • Condition indicators
  • Prognostic horizon
  • Digital twins
Example

PHM predicts a bearing will fail in about 200 operating hours, so the part is replaced at the next stop.

Why it matters

Prognostics and health management predicts how long a machine can run safely, so maintenance is planned before failure and downtime is reduced.

Where this is used

  • Estimating the remaining life of a gearbox from vibration trends.
  • Scheduling a bearing replacement based on a predicted failure date.
  • Alerting operators when a pump shows early signs of cavitation.

Frequently asked questions

What is Prognostics and health management?

Predicts remaining useful life from condition data.

Why is it important to understand prognostics and health management?

Prognostics and health management predicts how long a machine can run safely, so maintenance is planned before failure and downtime is reduced.

What is remaining useful life?

The estimated time or number of cycles before a component can no longer perform its function, given its current condition and expected use.

How does prognostics differ from simple monitoring?

Monitoring shows the current state, while prognostics predicts how that state will develop and when a failure is likely.

How is Prognostics and health management used in practice?

Typical applications include estimating the remaining life of a gearbox from vibration trends, scheduling a bearing replacement based on a predicted failure date and alerting operators when a pump shows early signs of cavitation.

What should I learn before Prognostics and health management?

Study "Model-based systems engineering" first (topic 101 of 102 in Manufacturing, Robotics & Systems). It covers the groundwork this topic builds on.

What are the key points of Prognostics and health management?

Condition indicators. Prognostic horizon. Digital twins.

Can you give an example of Prognostics and health management?

PHM predicts a bearing will fail in about 200 operating hours, so the part is replaced at the next stop.

What comes after Prognostics and health management?

This is the final topic in Manufacturing, Robotics & Systems.

How difficult is Prognostics and health management?

It is classed as Advanced in Manufacturing, Robotics & Systems (topic 102 of 102). It is an advanced topic. It assumes you are comfortable with the intermediate topics in Manufacturing, Robotics & Systems.

Learning path

Want to practise? Open the interactive course for quick checks, quizzes, simulations and progress tracking.

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