Preventive vs Predictive vs Breakdown Maintenance

Published on 10/18/2026 • Updated on 10/23/2026

A plant has three kinds of machines. Some are serviced by the calendar. Some are watched with instruments and serviced when the readings change. Some are left alone until they stop. Each approach is right for some machines and wrong for others, and the real skill is knowing which is which.

This guide explains preventive, predictive and breakdown maintenance in plain words, compares them in a table, gives examples from a typical plant, and shows how to choose a strategy for each asset. It uses assumed examples, not published statistics.

The three types in one line each

Corrective maintenance is the work done after a fault. Breakdown maintenance is the policy of letting a machine run until it fails, then repairing it. They are close, but the second is a choice, not an accident.

Breakdown maintenance

Breakdown maintenance means no planned work on the asset. You repair or replace it when it stops. It is cheap to start and expensive when applied to the wrong machine.

• Fits: low cost, easy to replace, no safety risk, a spare on the shelf, such as an office fan or a small pump with a standby.
• Does not fit: single points of failure, high repair cost, safety critical equipment.

The hidden cost is not the part. It is the stopped line, the overtime and the rush freight.

Preventive maintenance

Preventive maintenance is work done at fixed intervals, by days or running hours, to reduce the chance of failure. Oil changes, filter replacement, greasing, belt checks and calibration are typical.

• Fits: wear is predictable by time or use, failure is costly and the task is cheap.
• Does not fit: failures are random, or the task itself causes faults, such as opening a healthy gearbox.

Our guide on the preventive maintenance schedule shows how to build the list.

Predictive maintenance

Predictive maintenance, also called condition-based, uses measurement to decide when work is needed. Typical measures are vibration, temperature, oil analysis, current draw and ultrasound. When a reading crosses a limit, the team plans the repair.

• Fits: expensive or critical machines where failure gives warning, such as large motors, gearboxes, compressors and pumps.
• Does not fit: cheap assets where the sensor costs more than the machine, or failure modes that give no warning.

It needs instruments, trained people and a baseline for each machine. Many plants start with a handheld thermometer, a vibration pen or a thermal camera on a monthly round, before buying online sensors.

Side by side

Choosing a strategy for each asset

A plant almost always uses all three. The mix matters more than the label.

Thinking about cost the right way

The cheapest policy on paper is often the dearest in practice. Compare three costs for each important asset: the cost of the planned work, the cost of a breakdown and the chance of that breakdown. If a bearing costs Rs 2,000 to replace on schedule and a failure costs Rs 2 lakh in lost output, then even a one in ten chance of failure each year makes the schedule pay.

The figures above are an example, not data. Use your own numbers: the hourly value of the line, repair cost, overtime and the delay in restarting. Finance can help you set the hourly value, and it is worth fifteen minutes to agree on one number that you then use everywhere.

A simple way to decide

For each critical asset, ask what happens if it fails, how it usually fails and what warning it gives. If the answer to the third is a clear change in noise, heat or vibration, a condition check can catch it. If the answer is nothing, only a time-based task or a spare can protect you.

This is a light version of reliability-centred maintenance. You do not need a formal study to use the idea. A one hour workshop with the maintenance lead, an operator and a supervisor per critical machine is often enough.

People and skills for each approach

Breakdown work needs quick, skilled repairers. Preventive work needs planners and disciplined technicians who follow the card. Predictive work needs someone who can read the numbers and tell a normal trend from a warning. Do not expect one person to do all three well. Train one or two technicians in condition checks and let them build the rounds, while the rest follow the planned cards.

A worked example

The numbers are invented to show the split, not to set a target.

How to move from breakdown to planned

Do not try to change everything at once. Start with the machines that hurt most. List the last ten breakdowns, count which asset caused each and what it cost in lost hours. The top three assets deserve a preventive task or a condition check first. Our guide to MTTR and MTBF shows how to measure whether the change worked.

Keep the first tasks cheap and visible, and ask the operators to help, since they hear and feel changes first: a weekly walk-round with a checklist, a monthly temperature check with a handheld thermometer, a lubrication route. These cost little and often catch the first signs of trouble.

Common mistakes

Another mistake is treating predictive as a replacement for preventive. Some wear is best handled by a simple scheduled task.

A third is collecting readings with no limits. A number with no alert level is just a number.

A fourth is keeping the strategy in one person's head. Write the choice for each critical asset in the asset record, so a new supervisor can see the plan and the reason.

A 30-day review

Pick the right strategy for your top assets.

Review the results after three months using downtime hours, and share the result with the shift teams, and thank those who found the early warnings.

Five-minute self-check

Check your maintenance mix against these points.

Two or more no answers mean this is worth fixing before anything else on your list.

Reader Q&A

Bottom line

Breakdown, preventive and predictive maintenance are tools, not rivals. Use each for the assets where it pays.

Rank your assets, study how they fail and start with the machines that cost you most. Review the choice every year.

Author of the Blog Post

Aadeshwar Modi

Technical Content Writer at VisitorFlow

Aadeshwar Modi is a marketing technical content writer who loves writing on technology and AI topics.