Servicing a machine too early wastes money on parts and needless downtime. Servicing it too late means a breakdown in full production. Between the two lies the right moment, and that is the whole point of condition-based maintenance. Mimorian models equipment and captures the know-how of teams to help intervene at the right moment, on the right component. The real question is not 'preventive or not', it is 'which strategy for which equipment'. Here is how to decide.
Three strategies, not one
There are three ways to approach the maintenance of a piece of equipment, and none is right everywhere:
- Accepted run-to-failure: you let it run until it breaks. Acceptable on non-critical equipment that is cheap to stop and easy to restart.
- Systematic preventive maintenance: you service at fixed intervals, as a safeguard. Simple, but it leaves gaps between two visits and often drives over-maintenance.
- Condition-based maintenance: you intervene according to the actual state of the machine, neither before nor after. The most precise, but it requires knowing that state.
The common mistake is to apply the same strategy everywhere. The right approach is to choose according to criticality.
Choose according to equipment criticality
A piece of equipment whose stoppage is costly and which degrades gradually is the ideal candidate for condition-based maintenance. Non-critical, redundant or cheap-to-repair equipment does not justify the effort: run-to-failure is enough. Between the two, systematic preventive maintenance remains a reasonable compromise.
This grid avoids two symmetrical kinds of waste: instrumenting and monitoring machines that are not worth it, and letting a bottleneck asset break for lack of follow-up.
Fixed calendar schedules leave gaps
Systematic preventive maintenance has a structural flaw: it sees nothing between two visits. On a hydraulic unit serviced every six months, a pump can degrade for lack of maintenance matched to its actual state, and break in full production. Between the part, the emergency call-out and the line stoppage, the bill for a single episode climbs fast, in the order of several tens of thousands of euros.
The answer is not to service more often as a precaution, which is also costly. It is to move to condition-based maintenance on the equipment that deserves it.
The role of AI: anticipate and justify
To run condition-based maintenance, you need to know the actual state and be able to interpret it. By cross-referencing structured knowledge about a piece of equipment (its known failure modes, its history) with the monitoring of its state, AI spots the moment when a part deserves an intervention. Organisations that are mature in condition monitoring gain on average 9 % in machine availability [PwC/Mainnovation, 2018].
AI also brings a less visible benefit: it gives the team what it needs to justify a replacement in advance, with figures to back it up, to a management that hesitates to commit the spend. Acting at the right moment becomes a reasoned decision, not a gamble.
Conclusion
Condition-based maintenance is not a strategy to apply everywhere, it is the right answer for critical equipment that degrades gradually. The rest falls under systematic preventive maintenance or accepted run-to-failure. Chosen well by criticality, it protects production better at an equal maintenance budget.
For the complete framework of trustworthy AI in industrial maintenance, read our complete guide to trustworthy AI for industrial maintenance.