Not every machine on your site deserves the same attention.
That sounds obvious. Yet plenty of maintenance teams still spread their effort evenly, servicing a spare extract fan on the same schedule as the pump that keeps the whole line running.
Predictive maintenance fixes that. But only if you point it at the right equipment.
So which equipment benefits most from predictive maintenance? Here’s the short answer, followed by the detail that most guides skip.
The short answer
The equipment that benefits most from predictive maintenance is motor-driven rotating machinery: pumps, motors, fans, blowers, compressors, gearboxes, conveyors and generators. These machines wear out gradually, give off measurable warning signs weeks or months before failure, and often stop production when they fail.
The biggest returns come from rotating assets that are critical, expensive to lose, hard to reach, or energy-hungry. Tick more than one of those boxes and predictive maintenance usually pays for itself quickly.
Why rotating equipment tops the list
It fails slowly, and it tells you so
Think about a car tyre. It doesn’t go from brand new to bald overnight. The tread wears a little every week, and if you look, you can see it coming.
Rotating machinery works the same way. A bearing starts to wear. A shaft drifts slightly out of alignment. An impeller picks up damage. Each of these faults grows over time, and each one leaves a trace.
Engineers call the gap between the first detectable sign and the actual failure the P-F interval. The longer that window, the more useful predictive maintenance becomes. Rotating equipment tends to have a long one.
The warning signs are measurable
As faults develop in rotating machines, they change things you can measure:
- Vibration increases or changes pattern
- Temperature creeps up at bearings and windings
- Electrical current and voltage shift, because the motor has to work harder or unevenly
- Energy consumption rises as friction and inefficiency build
That last point gets overlooked. A developing fault doesn’t just threaten a breakdown. It quietly adds to your electricity bill every day it’s left alone.
Most failures aren’t age-related
Here’s the bit that surprises people. Classic reliability research, first done on aircraft components, found that most failures don’t follow a neat “it gets old, then it breaks” pattern. They happen at seemingly random points in an asset’s life.
That’s why fixed-schedule servicing often misses the problem. You can replace a bearing every 12 months and still lose a pump in month four. Predictive maintenance watches actual condition instead of the calendar, which is exactly what random failures need. Our guide to reliability centred maintenance vs CBM explains how this shapes a wider maintenance strategy.
The equipment that benefits most
Electric motors
Motors sit at the heart of almost every rotating system, which makes them the natural starting point. Bearing faults are the most common cause of motor failure, alongside stator winding problems, rotor bar defects and electrical imbalance.
The good news? A motor’s own electrical signature reveals a surprising amount about its health, and about the equipment it drives. More on that shortly.
Pumps
Pumps are some of the strongest candidates for predictive maintenance. They face cavitation, impeller wear, seal failures, blockages and bearing problems, and they’re often critical to the process.
Take one real example. An LNG tanker kept losing seawater pumps, each costing thousands of dollars to replace. Once permanent monitoring was fitted, it spotted a falling power factor and an unusual pattern around the pump’s vane pass frequency. Inspection found internal corrosion had eaten a hole through the pump casing. The repair cost a few hundred dollars, less than a tenth of a replacement.
The kicker: handheld vibration checks hadn’t picked it up, even on the day the pump came out of service.
Fans and blowers
Fans suffer from imbalance, blade build-up, belt wear and bearing faults. In power stations, forced draft and induced draft fans are critical. In tunnels and buildings, ventilation fans are often safety-critical and awkward to access, especially roof-mounted or duct-mounted units.
Compressors
Compressors are expensive, complex and usually central to production. When one fails, the cost includes the repair, the lost output and often a knock-on shutdown elsewhere. Predictive maintenance can pick up problems like internal rubbing, valve issues and bearing wear long before they cause a trip.
Gearboxes, conveyors and drivetrains
Misalignment, looseness, gear wear and belt tension problems all show up as changes in the load on the motor. Conveyors in particular can bring an entire site to a halt, so they punch above their weight when it comes to downtime cost.
Generators
Generators are often overlooked, but they’re rotating machines too. Faults can cross the line between electrical and mechanical, which makes them hard to pin down with a single technique. On offshore platforms and remote sites, a generator problem can affect everything else.
Hard-to-reach assets: where the biggest wins hide
Here’s where most guides stop short. The equipment that benefits most isn’t just the most critical. It’s often the equipment you can’t easily get to.
Think about:
- Submerged and borehole pumps
- In-tank and vertical cooling water pumps
- Duct-mounted and roof-mounted fans
- Cryogenic pumps under thick insulation
- Assets in hazardous or confined spaces
Traditional techniques like vibration analysis need a sensor on the machine, or a person standing next to it. For a pump 100 metres down a borehole, neither is practical. So these assets often get no monitoring at all, and they run until they fail.
That’s where electrical monitoring changes the game. Because it measures from the motor’s supply in the switchroom, it doesn’t matter where the machine is.
One water utility put this to the test. Monitoring flagged an impeller problem on a borehole pump and predicted when it would need replacing. To check the prediction, the pump was left running. It failed within a couple of days of the predicted date.
What about switchgear, transformers and boilers?
These “balance-of-plant” assets do benefit from condition tracking, and you’ll see them on most lists. But it’s worth being clear about how.
Switchgear and electrical connections are usually checked with thermal imaging, which spots hot joints and overloaded circuits before they cause a fire or trip. Transformers are often monitored with oil testing. Boilers and heat exchangers are typically covered by inspection and performance tracking.
These are all useful. But they’re mostly periodic checks rather than continuous predictive maintenance, and the failure patterns aren’t as clear-cut as those in rotating machinery. If you’re deciding where to start, rotating equipment usually delivers faster, clearer returns.
Equipment that benefits least
Predictive maintenance isn’t worth it for everything. Be honest about these:
- Cheap, non-critical assets. If a small fan costs less to replace than to monitor, and losing it doesn’t stop anything, run it to failure.
- Assets with full redundancy. If a standby unit takes over instantly and seamlessly, the case is weaker (though monitoring the duty unit still helps plan repairs).
- Equipment with truly sudden failure modes. Some electronics fail with little or no warning, so there’s nothing to predict.
- Rarely used kit where condition changes too slowly to matter.
Knowing what to leave out is just as important as knowing what to include. It keeps your budget pointed at the assets that actually matter.
How to decide which of your assets to prioritise
Not sure where to start? Score each asset against five simple questions.
- What happens if it fails? Does it stop production, create a safety risk or breach a service obligation?
- How much does downtime cost per hour? Include lost output, overtime, scrap and emergency call-outs.
- How long would a replacement take? Long lead times on pumps, motors or gearboxes turn a failure into weeks of disruption.
- Can you actually reach it? Inaccessible assets get missed by manual checks.
- How much energy does it use? Large motors running faulty waste money every single day.
Assets that score high on three or more deserve predictive maintenance first. Our benefits calculations can help you put real numbers against the business case.
Matching the technique to the equipment
Different condition monitoring techniques suit different equipment. Here’s a quick comparison.
| Technique | Best for | Limitations |
| Vibration analysis | Bearings, imbalance and misalignment on accessible machines | Needs sensors on the machine or manual rounds; struggles with inaccessible assets |
| Thermal imaging | Switchgear, electrical connections, hot bearings | Periodic snapshots; limited insight into mechanical faults |
| Oil analysis | Gearboxes, engines, hydraulics | Lab-based and periodic; only works on lubricated systems |
| Ultrasound | Leaks, early bearing wear, electrical discharge | Usually handheld and periodic |
| Electrical signature analysis (MBVI) | Motors and everything they drive: pumps, fans, compressors, conveyors, generators | Applies to electrically driven equipment |
Faraday Predictive uses MBVI (Model-Based Voltage and Current) technology, an advanced form of electrical signature analysis. It treats the motor as the sensor, picking up mechanical, electrical and process faults across the motor, drivetrain and driven machine, all from the switchgear. It also measures how much energy each fault is wasting. You can read more in our guide to MBVI technology.
Still weighing up the terminology? Our article on condition monitoring vs predictive maintenance clears up the difference.
A real example: £300k saved from half an hour of testing
An oil and gas facility had already suffered lube oil pump problems that led to an unplanned shutdown and flaring. As a precaution, the team tested their other pumps with a portable MBVI kit.
The test found a bearing and rubbing problem on one pump. On closer inspection, it was linked to a failing seal that was releasing lubricant. The bearing and seal were replaced at low cost.
The previous incident had been conservatively estimated at £300k to £500k. The test that prevented a repeat took about half an hour.
That’s the case for predictive maintenance on critical pumps in a nutshell.
Where to start
You don’t need to monitor everything at once. Most sites start with a handful of critical assets and grow from there.
Faraday Predictive offers three ways in:
- Inpod permanent condition monitoring for continuous, 24/7 monitoring of your most critical machines, installed in the switchroom with no sensors on the equipment.
- P100 portable condition monitoring for on-the-spot testing across multiple assets, ideal for troubleshooting or building a business case.
- On-site diagnostic survey where our engineers test your critical machines and report back on what we find.
Want to see how it would work on your equipment? Book a free 10-minute demo and we’ll talk through your assets with you.
Summary
The equipment that benefits most from predictive maintenance is motor-driven rotating machinery: pumps, motors, fans, compressors, gearboxes, conveyors and generators. These assets wear gradually, give clear early warning signs and often cause expensive downtime when they fail.
The biggest wins come from assets that are critical, costly to replace, hard to reach or energy-hungry. Start there, skip the cheap and redundant kit, and choose a monitoring technique that suits the equipment, including the machines you can’t easily get to.
Frequently asked questions
Start with critical rotating equipment whose failure would stop production, create a safety risk or take weeks to replace. Pumps, motors, compressors and conveyors usually top the list. Hard-to-reach and energy-intensive assets should also rank highly, because they’re often unmonitored and wasting energy when faults develop.
It depends on what the motor drives. A small motor powering a critical pump or conveyor can justify monitoring, because downtime costs far more than the motor itself. A small motor on a non-critical, easily replaced fan usually doesn’t. Judge by the impact of failure, not the size of the motor.
Yes. Electrical signature analysis measures the motor’s voltage and current from the switchroom, so it works regardless of where the pump sits. That makes submerged, borehole and in-tank pumps practical to monitor, even though vibration sensors or manual checks can’t easily reach them.
Bearing faults are the most common cause of failure in electric motors and much of the rotating equipment they drive. Misalignment, imbalance and looseness often speed up bearing wear, so catching those early prevents many bearing failures. Predictive maintenance can spot all of these long before a breakdown.
Not necessarily. Traditional vibration monitoring needs sensors on each machine, but electrical monitoring such as MBVI works from the motor’s supply cables in the switchroom. Nothing is fitted to the equipment itself, which cuts installation time and makes it possible to cover assets that are otherwise hard to reach.