Maintenance strategies compared

Every maintenance team answers the same question for each machine: when do we do the work? Before it fails, on a schedule? When it shows signs of wear? When a forecast says it will fail soon? Or after it breaks? Each answer is a maintenance strategy. Most plants use all four, on different machines.

Reactive maintenance

Run the asset until it fails, then repair or replace it. This is also called run-to-failure or breakdown maintenance, and it is one form of corrective maintenance.

It needs no planning and spends nothing on inspections. The cost comes later: unplanned downtime, rushed parts, overtime, and sometimes damage to other components when a part fails hard.

Reactive maintenance is the right choice when a failure is cheap, safe, and quick to fix. A light fitting in a storeroom or a desk fan does not need an inspection plan. It is the wrong choice for a machine that stops a whole line.

Preventive maintenance

Do the work at fixed intervals of time or usage: every three months, every 500 operating hours, every 10,000 cycles. See preventive maintenance.

It is simple to plan and easy to explain. Work can be scheduled around production, and parts can be ordered ahead. It works best for wear that is related to age or use, such as lubrication, filters, belts, and seals.

Its weakness is that many failures are not related to age. A bearing may fail early because of a bad installation, or run well past its interval. A fixed schedule replaces some parts too early and misses others.

Condition-based maintenance

Measure the condition of the asset and act when the measurement shows a problem. See condition-based maintenance.

The measurements can be simple, such as a technician noting oil level and listening for noise, or instrumented, such as vibration or temperature readings. The work is done when it is needed, not before and, ideally, not after.

This only helps for failures that give a warning, and only if you check more often than the warning period. If a gearbox gives two weeks of rising vibration before it fails, a monthly check will miss half of the warnings.

Predictive maintenance

Use trends in condition data to forecast when the asset will fail, and plan the work for a convenient time before that. See predictive maintenance.

This gives the longest lead time and the best chance to fit the repair into a planned stop. It also needs the most: sensors or regular measurements, data that is stored and comparable, and people or models that can read the trend.

Choosing a strategy per asset

There is no single best strategy. A common way to choose is to ask a few questions for each asset or failure mode:

1. What happens when it fails? Safety risk, environmental risk, production loss, or just an inconvenience.
2. Does the failure give a warning? If yes, condition checks are possible. If no, a fixed schedule or a redundant unit may be the only protection.
3. Is the failure related to age or use? If yes, a fixed interval can prevent it.
4. What does prevention cost compared with the failure? A daily inspection of a cheap, non-critical pump costs more than the pump.

The answers usually land in a pattern. Critical machines with expensive, slow-to-replace parts get condition-based or predictive maintenance. Wear items get preventive tasks. Cheap, non-critical items run to failure, with a spare on the shelf.

Formal methods such as reliability-centered maintenance (RCM) work through these questions for every failure mode of a system. Most teams do a lighter version for their most important machines first.

Signs the mix is wrong

• Most work orders are emergencies, and the plan is always interrupted.
• The same failures keep coming back. That is a job for root cause analysis, not more repairs.
• PM tasks find nothing, month after month. The interval may be too short or the task may not matter.
• Failures happen shortly after PM work. The work itself may be introducing faults.

What every strategy needs

Every strategy depends on knowing what happened last time. A preventive plan is tuned from what PM tasks found. A condition-based plan needs earlier readings to compare. A predictive model needs recorded failures to learn from. Even reactive maintenance goes faster when the technician can see how the same fault was fixed before.

That is why the quality of work order records matters more than the choice of strategy. See Why maintenance knowledge gets lost at the machine.