Reactive (run-to-failure) maintenance
Reactive maintenance means fixing or replacing equipment only after it fails, no scheduled inspections or servicing in between. It requires the least planning and the lowest ongoing labor cost, which makes it a reasonable default for low-value equipment that is cheap and fast to replace, where a failure causes no safety risk and minimal disruption.
For equipment where downtime is expensive, production-critical machinery, refrigeration holding perishable stock, safety equipment, reactive maintenance is usually the most expensive strategy overall despite its low day-to-day cost: an unplanned failure means rush parts, overtime labor, and lost output, all of which typically cost more than a scheduled repair would have.
Preventive maintenance
Preventive maintenance services equipment on a fixed schedule, regardless of its actual current condition, to catch wear before it causes a failure. It comes in two forms: time-based (every 30, 60, or 90 days, or annually) and usage-based (every 500 operating hours, every 10,000 cycles), whichever unit fits how the equipment actually wears.
The tradeoff is that a fixed schedule sometimes services equipment that did not need it yet, and sometimes misses a failure that develops faster than the schedule assumed. It remains the most common strategy because it is far simpler to plan and staff than predictive monitoring, while still catching most wear-related failures before they happen.
Predictive maintenance
Predictive maintenance uses sensor data, vibration, temperature, sound, or output patterns, to estimate when a specific piece of equipment is actually approaching failure, rather than assuming a fixed schedule. Work is scheduled around the predicted failure window, not a calendar date, which means fewer unnecessary services and fewer surprise breakdowns than either reactive or preventive maintenance alone.
The tradeoff is upfront cost and complexity: predictive maintenance needs monitoring sensors and enough historical data to build a reliable prediction, which is only worth the investment for equipment where downtime is expensive enough to justify it, typically production-critical or safety-critical machinery.
Condition-based maintenance
Condition-based maintenance triggers a service the moment a measured condition crosses a defined threshold, a temperature limit, a vibration level, an oil contamination reading, rather than predicting a future failure window the way predictive maintenance does. It sits between preventive and predictive: more responsive to actual equipment state than a fixed schedule, but simpler to implement than a full predictive model since it reacts to a single threshold instead of a trained prediction.
This works well for equipment with a clear, measurable early-warning signal, a coolant temperature that creeps up before a compressor fails, for example, without needing the historical data volume a predictive model requires.
Choosing a maintenance strategy by equipment criticality
Most operations do not pick one strategy for everything, they match the strategy to each asset's criticality and cost of failure. Rank equipment by how disruptive or costly its failure would be, then apply a heavier strategy only where that cost justifies it.
- High criticality (production line stoppage, safety risk, spoilage of perishable stock): predictive or condition-based monitoring, where the investment is justified by the cost of an unplanned failure
- Moderate criticality (equipment with replaceable capacity, delay-tolerant but not free): preventive maintenance on a time- or usage-based schedule
- Low criticality (cheap, fast to replace, no safety or output impact): reactive maintenance, since scheduling upkeep would cost more than occasionally replacing the item
Using QR codes to run any of these strategies
Whichever strategy applies to a given asset, the practical bottleneck is usually the same: getting maintenance history and the next due date in front of the technician standing next to the actual equipment. A QR code tag on each asset solves this directly, scanning it with any phone pulls up that unit's full service history, its current status, and when its next preventive check or inspection is due, without searching a separate system or asking someone back at the office.
This matters most for preventive schedules (the technician sees immediately whether a service is overdue) and condition-based triggers (a scan can log a reading against the asset's threshold on the spot). See how to use QR codes for inventory for the setup details, static versus dynamic codes, and what to encode.
A worked example: restaurant and food-service equipment
Restaurant and food-service equipment illustrates why matching strategy to criticality matters. A walk-in cooler or reach-in refrigerator is high criticality by this framework, its failure risks spoiling an entire inventory of perishable stock and can trigger a health code violation, so it warrants condition-based monitoring (a temperature alert before spoilage starts) or at minimum a strict preventive schedule, not reactive maintenance.
A dish machine or a prep table, by contrast, causes inconvenience but not stock loss if it fails, making preventive maintenance on a routine schedule sufficient. Applying the same reactive approach to both, waiting for either to break, treats a spoilage-and-compliance risk the same as a minor inconvenience, which is exactly the kind of mismatch a criticality-based strategy is meant to avoid.
Logging the work: what a maintenance record needs
Whatever strategy is in use, each service needs a record: the asset, the date, what was done, parts used, and the next due date or trigger condition, kept against the specific unit rather than a general note. Without this, condition-based and predictive strategies have no baseline to compare readings against, and preventive schedules drift once nobody can say for certain when a unit was last serviced.
This is a separate concern from choosing a strategy, but the two depend on each other: a condition-based threshold is only useful if past readings are logged somewhere to compare against. See the equipment maintenance log template for a ready-to-use record format, or equipment maintenance software for tracking this alongside live asset and parts data instead of a static sheet.
Track maintenance status alongside your assets and parts
StockFlow keeps service history, overdue alerts, and spare parts stock in one place, so a scanned QR code shows a technician exactly what an asset needs, whichever maintenance strategy applies to it.
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