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Predictive maintenance ROI

What does an unexpected stop cost you?

A breakdown costs more than a repair. It can stop production, tie up your team, and delay orders. Catching equipment problems earlier gives you time to plan the work. See what that could save your operation.

Control Seat sensor mounted on a blue industrial motor
Control Seat sensor mounted on an industrial motor.
Build the business case

Start with the costs of a breakdown.

Less downtime means more time producing. Planned repairs can also reduce emergency costs and product losses.

CostWhat to count
Lost productionThe value you lose while equipment is down and orders cannot move.
Emergency repairsExtra overtime, rush parts, and callout fees.
Scrap or spoilageMaterials or finished products lost during a breakdown.
Cost of monitoringSensors, installation, software, connectivity, and support.
Your potential savings

Could monitoring pay for itself?

We’ve filled in a starting estimate based on avoiding one eight-hour stoppage a year, at $2,500 per hour. Adjust any number to see the value for your operation.

Your estimated return

Downtime avoided each year
8 hours
Estimated annual savings
$20,000
First-year net savings
$11,000
First-year ROI
122%
Estimated payback period
2.6 months

Adjust the numbers to match your equipment and budget.

How we calculate the estimate

Potential annual savings = avoided downtime hours × cost per hour + other costs avoided.

First-year net savings = potential annual savings − annual monitoring cost − upfront cost.

First-year ROI compares those net savings with the total first-year cost. Payback estimates how long savings after ongoing costs would take to cover the upfront cost.

Starting values are estimates. Your quote and actual savings will depend on your site.

Case studies & research

What other manufacturers have found.

Published examples show how monitoring helps teams find equipment problems and reduce costs. These examples describe other manufacturers’ programs.

3M · Published case study$32,000/year

Estimated savings from monitoring steam traps.

At 3M’s Brookings plant, sensors on 50 steam traps helped maintenance find failures sooner. The site estimated $32,000 in annual energy savings and reduced the average time to discover a failed trap from 33 days to 12.

Read the published case study
Saint-Gobain · Published case studyA stuck valve

Found through equipment run-time data.

At a ceramics plant, monitoring revealed that a blower was running for 30 minutes on a batch that needed seven. The team found and repaired an intermittently stuck valve, then added alarms for unusually long run times.

Read the published case study
PNNL · Independent research8–12%

Estimated maintenance-cost savings.

Pacific Northwest National Laboratory summarizes earlier studies that estimated this saving for predictive maintenance compared with preventive maintenance alone.

Read the maintenance guidance
NIST · Independent research18.5%

Less downtime in a survey comparison.

Manufacturers using more predictive maintenance reported less unplanned downtime than those using more preventive maintenance. NIST treats this small-group comparison as exploratory evidence.

Read the manufacturing study
Prove the value at your site

Start with a few important machines.

01

Record what happens today.

Choose machines with costly stops. Note recent downtime, emergency repairs, and production losses before monitoring begins.

02

Track findings and repairs.

Use the readings to investigate developing problems. Record what your team finds and the repairs it plans.

03

Review the results.

Compare downtime and emergency repair costs before and after monitoring to see where it is making a difference.

Let’s talk about your equipment.

Tell us what you run. We’ll help you choose where to start.

Talk to our team