Why Machines Fail Over Time and How Predictive Maintenance Extends Life

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The machines do not fail - the risk that their fault follows an estimated pattern known as a bathtub. Understanding this helps industries to plan maintenance and help avoid expensive surprises.

Key Takeaways

  • Machine failure risk is highest at startup and again during wear-out.
  • The bathtub curve illustrates three distinct phases of machine life.
  • Different applications and the environment are accelerated or slow in these stages.
  • Predictive Maintenance (PdM) ensures failures are caught quickly regardless of the machine's age.

Three stages of machine life

Each industrial machine - a pump, fan or motor - experiences three stages of reliability:

  1. Early Life (Infant Mortality Phase)

    • High probability of failure.
    • Causes: installation errors, misalignment, improper lubrication, manufacturing defects.
    • Duration: first few weeks to months.
  2. Normal Life (Useful Life Phase)
    • Failure probability stabilizes and remains low.
    • Machines run reliably if operated within design limits.
    • This is where maintenance strategies make the biggest impact.
  3. Wear-Out Phase (End of Life)
    • Failure probability rises again.
    • Causes: fatigue, corrosion, wear, and aging of parts.
    • Often requires major overhauls, replacements, or redesign.

Example: Centrifugal Pump Life

  • A single-stage horizontal split case centrifugal pump running on clean water may perform reliably for 18 months or more.
  • The same pump handling slurry may fail much earlier due to abrasion, erosion, and seal wear.

This shows that Mean Time to Failure (MTTF) and Mean Time Between Failures (MTBF) are not fixed numbers - they vary depending on the application.

Why PdM Matters at Every Phase

Predictive Maintenance tools (like vibration analysis, infrared thermography, and ultrasound) provide protection across all life stages:

  • Early Life: Detect installation issues before they cause infant failures.
  • Normal Life: Monitor hidden degradation, prevent sudden breakdowns, and extend MTBF.
  • Wear-Out Phase: Predict when components will fail so replacements can be planned, not rushed.

Business Risks Without Understanding Failure Probability

If plants ignore these failure patterns, they face:

  • Unexpected downtime during startup.
  • Overconfidence during normal life (leading to surprise breakdowns).
  • High repair costs at wear-out.
  • Reduced trust in both equipment and maintenance teams.

Final Word: Reliability is a Curve not a Constant

Failure probability isn’t flat - it changes with machine age and application.
By understanding the bathtub curve and using PdM, industries can align their maintenance with reality:

  • Catch infant failures early.
  • Maintain reliability in normal life.
  • Prepare for wear-out proactively.

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