In fleet management, choosing the right type of maintenance is a decision that directly impacts costs, safety, and vehicle availability. Two of the most well-known approaches are predictive maintenance and corrective maintenance, each with advantages and limitations.
While predictive relies on technology and data analysis to intervene before a failure occurs, corrective waits until the breakdown is evident to repair it. The key is understanding their differences and deciding which to apply based on the fleet profile and needs.
Predictive maintenance uses sensor data, telemetry, and statistical analysis to predict when a component will fail. Fixed intervals are not followed; instead, action is taken based on the actual condition of each part or system.
Example: A sensor detects that a bearing temperature is rising above normal. Before it breaks, a replacement is scheduled.
Advantages:
Disadvantages:
Corrective maintenance consists of repairing equipment or a vehicle after the failure has already occurred. It can be planned (if something is detected as failing but the vehicle remains operational) or unplanned (when it occurs unexpectedly).
Example: A truck stops because the timing belt broke. The vehicle is out of service until repaired.
Advantages:
Disadvantages:
Negative impact on service and company image.
A transport company with 150 trucks shifted from an 80% corrective / 20% preventive scheme to 60% predictive / 40% corrective.
Results in 12 months:
Most of the most efficient transport companies do not choose between one or the other. They combine both approaches according to the criticality of each asset.
A balanced model could be:
The answer to “which is better?” is not absolute. It depends on the fleet type, available resources, and maintenance strategy.
However, with advances in IoT, artificial intelligence, and fleet management platforms, predictive is more cost-effective in the long run, but corrective still has a place in a balanced strategy.