A plant manager who says "we run a good maintenance program" without a benchmark is running on belief. Seven numbers — cost per MWh, equivalent availability, equivalent forced outage rate, backlog, PM compliance, mean time between failures and mean time to repair — place the program against industry peers and against last year. The gap between the plant and the top-quartile peer is the maintenance organization's work-list. This guide walks the metric set, the quartile ladder, the peer-group logic and the benchmarking cadence. OXMAINT AI is the AI-powered power plant maintenance software that holds the seven metrics live, re-benches them monthly against the peer group and keeps the gap-closure plan on the same record as the WOs it depends on.
POWER PLANT MAINTENANCE BENCHMARKING · COST · AVAILABILITY · RELIABILITY · 2026
Power Plant Maintenance Benchmarking: Cost, Availability & Reliability
Seven metrics, three quartiles, one scorecard. OXMAINT AI holds the plant's live benchmark against the right peer group, tracks the gap to top-quartile monthly, and keeps every gap-closure action on the same WO backlog it is being measured by.
4
quartile bands · top / 2 / 3 / bottom
1
peer group chosen by fuel & size
M
monthly cadence, not annual survey
The Seven Metrics — What Each One Measures
A benchmark set with more than seven metrics is one nobody reads. These seven cover cost, availability and reliability without overlap, and every one has an industry-standard definition. OXMAINT AI stores each with its definition on the record so the peer-group comparison is apples to apples — spin up the standard benchmark set in OXMAINT AI.
COST
Maintenance $ / MWh
Total O&M spend on maintenance divided by net generation. Fuel excluded. Labor, parts, outside services, outage amortized.
COST
Maintenance $ / kW installed
Annual maintenance spend divided by nameplate kW. The capacity-normalized view, useful across different capacity factors.
AVAIL
Equivalent Availability (EAF)
NERC GADS definition: hours available at full capability as a share of period hours, derated hours penalized proportionally.
AVAIL
Equivalent Forced Outage (EFOR)
Forced-outage and derate hours divided by service hours plus forced-outage hours. The "surprise rate" of the plant.
RELIAB
PM compliance %
PMs completed inside their window divided by PMs scheduled. The leading indicator for next quarter's EFOR.
RELIAB
Backlog weeks
Open backlog hours divided by craft-hour weekly capacity. 4-6 weeks is healthy; above 10 is a backlog debt problem.
RELIAB
MTBF & MTTR
Mean Time Between Failures (reliability direction of travel) and Mean Time To Repair (team capability). Reported together.
The Quartile Ladder — Where The Plant Sits
Each metric lives on a quartile ladder: top, second, third, bottom. The ladder shifts by fuel class and plant size; the ranges below are mid-market working numbers for a sub-critical pulverized-coal unit as an illustrative baseline. OXMAINT AI loads the right ladder per unit automatically.
Metric
Top quartile
2nd quartile
3rd quartile
Bottom
Maint $/MWh
< $3.5
$3.5-5.0
$5.0-7.0
> $7.0
Maint $/kW-yr
< $25
$25-35
$35-50
> $50
EAF %
> 90
86-90
80-86
< 80
PM compliance
> 95
90-95
80-90
< 80
Backlog weeks
4-6
6-8
8-12
> 12
MTBF (critical)
> 1800 h
1200-1800
600-1200
< 600
Plant Benchmark Scorecard — One Screen, Seven Markers
The scorecard shows the plant's current reading, the peer-group median and the top-quartile line. Each bar carries three markers so the gap is visible without a report. OXMAINT AI renders this live from the WO log and the generation record.
UNIT 2 · PEER GROUP: SUB-CRITICAL COAL 300-600 MW · LAST 12 MONTHS
Maint $/MWh
$5.80
Maint $/kW-yr
$38
EAF %
88.3%
EFOR %
7.4%
PM compliance
92%
Backlog weeks
9.2 w
MTBF critical
1,080 h
You
Peer median
Top quartile
4 of 7 metrics in 3rd quartile — backlog debt and MTBF the two biggest gaps
Peer Group Logic — Who To Benchmark Against
A benchmark against the wrong peer group is worse than no benchmark. Four variables decide the peer group; OXMAINT AI auto-matches on all four and lets the plant override.
01
Fuel & prime-mover class
Sub-critical coal, super-critical coal, gas CCGT, gas peaker, nuclear PWR, nuclear BWR, hydro, solar, wind. The single most important variable.
02
Unit size band
< 200 MW / 200-500 MW / 500-800 MW / > 800 MW. Larger units have lower $/MWh baseline but higher outage cost.
03
Capacity factor band
Baseload (> 70%), intermediate (30-70%), cycling / peaker (< 30%). Cycling units run higher $/MWh and lower EAF naturally.
04
Age band
< 15 yr / 15-30 yr / 30-45 yr / > 45 yr. Mid-life units carry the heaviest maintenance load; benchmark against age, not just class.
Benchmarking Cadence — Monthly, Not Annual
An annual benchmarking survey is a report that lands in a drawer. The modern cadence is monthly — the metric computes from the live WO log and generation record, the peer-group median rebuilds, and the gap-closure plan carries over as live WOs.
Daily
Operational feed
Generation, EFOR events and WO closures land in the live data layer.
→
Weekly
Backlog & PM compliance
Backlog weeks and PM compliance refreshed; the two leading indicators the plant can move within the month.
→
Monthly
Full benchmark re-run
All seven metrics vs peer-group median and top quartile; gap-closure items raised as WOs for the next month.
→
Quarterly
Peer group refresh
Peer-group membership refreshed, outlier units removed, trending direction reviewed with plant leadership.
The Gap To Top Quartile Is Your Maintenance Work-List.
A benchmark that shows "backlog is 9.2 weeks against top-quartile 4.5 weeks" is not a conclusion, it is a work-list. OXMAINT AI converts every gap into tagged WOs so the next monthly re-bench measures what the plant actually did.
Gap Waterfall — What Closing The Gap Looks Like
Every % of EFOR improvement, every day of backlog cleared, every point of PM compliance gained has an owning action. The waterfall below is the typical shape of a 12-month gap-closure plan for a 3rd-quartile unit climbing to top-quartile.
Start of year
Composite index 60
+ Backlog cleared (6 mo)
+ 12
+ PM compliance to 95%
+ 8
+ Predictive sensors on top 10 assets
+ 10
End of year
Composite index 90 · top quartile
Benchmarking Across Fuel Classes — Reference Ranges
The benchmark ladder shifts materially by fuel class. The ranges below are working mid-market numbers for the headline metrics; OXMAINT AI holds the right ladder per asset so the comparison is always like-for-like.
Fuel class
Top-Q EAF
Top-Q EFOR
Top-Q $/MWh
Capacity factor
Sub-critical coal
> 90%
< 4%
< $3.5
60-85%
Super-critical coal
> 91%
< 4%
< $3.0
70-90%
CCGT baseload
> 93%
< 2%
< $2.5
50-85%
Gas peaker
> 95%
< 3%
< $4.5
< 25%
Nuclear
> 92%
< 2%
< $7.5
> 90%
Hydro
> 92%
< 2%
< $4.0
35-55%
How OXMAINT AI Runs The Benchmarking Program
The seven-metric computation, peer-group matching, quartile ladder, scorecard, gap waterfall and monthly re-bench all live natively in the OXMAINT AI power plant maintenance software — open an account and generate the first benchmark month in OXMAINT AI.
Live Metric Computation
All seven metrics computed from the live WO log and generation data — no month-end survey, no spreadsheet.
Peer-Group Match
Four-variable match on fuel class, size, capacity factor and age; override available where plant leadership picks a tighter cohort.
Quartile Scorecard
One-screen scorecard with your-median-top markers on every bar; monthly refresh with trend arrow.
Gap-Closure WOs
Each gap converts to tagged WOs with target metric and target delta — next re-bench measures what the plant actually did.
Fleet View
For multi-unit operators, every unit vs its own peer group side-by-side — so corporate sees where the fleet gap really sits.
Audit Trail
Every metric carries its definition and the WO log it was computed from — so the number survives external audit.
Frequently Asked Questions
Isn't annual benchmarking enough?
Annual lands as a report, monthly lands as a plan. The gap-closure actions a plant can take — backlog, PM compliance, outage scope — move in weeks, not years. OXMAINT AI re-benches monthly from the live data so each month's plan starts with where the plant actually stands.
Where do the peer-group numbers come from?
For regulated US fleets, NERC GADS is the public backbone for availability and forced-outage data. Cost benchmarks typically come from utility-group studies and industry trade bodies. OXMAINT AI blends public datasets with the plant's own anonymized fleet data where available.
Which single metric gives the fastest insight?
Backlog weeks. It is a leading indicator for next quarter's EFOR, it computes from the WO log directly, and it is the metric a plant can move within a month without outage scope changes. The second-fastest is PM compliance for the same reason.
What if the plant is already top-quartile?
Benchmark against yourself. Month-over-month trend of your composite index is the second-order benchmark for a plant that is already at or near the frontier. OXMAINT AI stores the historical scorecard and renders the trend as a chart.
Measure The Program With The Same Data That Runs It.
Load the seven-metric benchmark into the OXMAINT AI power plant maintenance software — live computation, peer-group match, quartile scorecard, gap waterfall and the gap-closure WOs tagged on the same backlog. The next monthly re-bench measures what the plant actually did.
