Aircraft Reliability – Component Removal – CAMO Considerations

Aircraft Reliability – Component Removal – CAMO Considerations

Aircraft Reliability is an important way to track both trends and ensure that a maintenance plan is appropriate for the aircraft and its operating environment.

When we mention component removals for reliability purposes, we are not concerned about planned routine component removals; we need to analyse however any component that is removed because of a failure/defect or suspected failure/defect.

A component that fails a check, such as operational of functional check, as part of a system or individually – that is what we need to analyse – this failure is not scheduled, and we did not expect the component to fail.

A scheduled removal is one where the component or item is removed because of the life reaching, or close to reaching a determined threshold – we expect this to occur. It is regardless of the item or component’s ability to perform or pass any given operational and functional checks.

It is in this area of unscheduled and unexpected that awareness and removal procedures are particularly important. Separating and managing this logic can be difficult – consider a part removed during a scheduled task is not removed “Un Scheduled” but rather removed as “Scheduled” – depending on the MIS (Maintenance Information System) this can be hard to determine, and users can often remove parts that are scheduled as unscheduled making metrics harder to capture accurately.

Consider the following examples –

A routine battery change – this is scheduled and should not be considered as an item to investigate.

What about worn wheels and brakes (not including failures such as blow outs), but a worn tyre or a worn brake – we expect these items to wear and be replaced.

Passenger equipment such as a first aid kit, do you need to consider reliability if these items are replaced; not as they are based on attrition and cabin crew guidance, if not expiry dates.

You can see from the examples that component reliability requires a lot of awareness to ensure your data becomes meaningful information.

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