5. Reliability and asset performance

17 steps

1. Step 1 of 17
   Reactive (Run-to-Failure) Maintenance
   Fixing things after they break. Sensible for cheap, non-critical items, costly when used for critical ones.
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2. Step 2 of 17
   Preventive Maintenance
   Doing maintenance on a fixed schedule or usage interval to reduce the chance of failure.
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3. Step 3 of 17
   Condition-based Maintenance (CBM)
   Doing maintenance when measurements show it is needed, instead of on a fixed calendar.
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4. Step 4 of 17
   P-F Curve
   A model showing that most failures give warning signs: point P is where a potential failure can first be detected and point F is where it actually fails. The gap is your window to act.
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5. Step 5 of 17
   Predictive Maintenance
   Using data and models to forecast failures so work happens just before it is needed.
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6. Step 6 of 17
   Criticality Analysis
   Ranking assets by how much their failure would affect safety, environment, service and cost, so effort goes where it matters.
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7. Step 7 of 17
   FMEA / FMECA
   Failure Modes and Effects (and Criticality) Analysis: listing each way an asset can fail, what happens when it does, and how serious it is.
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8. Step 8 of 17
   Reliability-Centered Maintenance (RCM)
   A structured method for deciding the right maintenance for each asset based on its functions, how it can fail and the consequences of failure.
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9. Step 9 of 17
   Failure Code / Failure Class
   A structured hierarchy used to record why something failed. It runs from failure class to problem to cause to remedy.
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10. Step 10 of 17
    MTBF (Mean Time Between Failures)
    The average time an asset runs between failures. Higher is better.
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11. Step 11 of 17
    MTTR (Mean Time to Repair)
    The average time it takes to repair an asset after a failure. Lower is better.
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12. Step 12 of 17
    Asset Performance Management (APM)
    Using live data, health scoring and prediction to keep assets reliable and spend money where it matters most. In MAS this is mainly Monitor, Health and Predict working with Manage.
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13. Step 13 of 17
    Maximo Monitor
    The MAS application for collecting and watching live data from sensors and systems, detecting anomalies and showing it on dashboards.
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14. Step 14 of 17
    Maximo Health
    The MAS application that gives each asset a health score and helps decide what to repair, replace or watch based on condition, risk and cost.
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15. Step 15 of 17
    Health Score
    A number, usually 0 to 100, showing an asset's overall condition, calculated from contributors you choose.
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16. Step 16 of 17
    Maximo Predict
    The MAS application that uses machine learning models to predict things like failure probability, predicted failure dates and anomalies.
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17. Step 17 of 17
    Maximo Visual Inspection (MVI)
    The MAS application for training computer vision models to spot defects, corrosion, leaks or other conditions in images and video.
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