Most power plant reliability teams can name their KPIs but cannot say, with confidence, whether last month's MTBF of 740 hours is good or a warning sign. That ambiguity is expensive: unplanned equipment failures quietly drain 4–8% of annual generation capacity at a typical fossil or combined-cycle plant, and the gap is rarely a technology problem — it is a benchmarking problem. Reliability leaders who track MTBF, MTTR, PM compliance, and OEE against real industry reference points consistently outperform peers who only track the numbers without context. OxMaint's Analytics & Reporting module calculates every one of these KPIs automatically from work order and asset data, so your team spends time improving the number instead of producing it. Book a 30-minute demo to see your own plant's reliability data benchmarked live.
4–8%
of annual generation capacity lost to unplanned failures at the average plant
800 hrs
MTBF threshold — below this, most plants have an active PM program gap
85%
planned maintenance percentage seen in top-quartile reliability programs
25%
higher asset uptime for plants using standardized KPI dashboards, per McKinsey
The Five KPIs That Actually Predict Failure
Tracking everything creates noise. These five tell reliability engineers exactly what to fix and when.
01
MTBF
Mean Time Between Failures
Average run-time before an unplanned failure. A falling trend over consecutive months signals PM backlog or asset aging — three to six months before it shows up as downtime.
02
MTTR
Mean Time To Repair
Average time from failure detection to restored service. Climbing past 10 hours usually means spare parts staging or diagnostic workflow problems, not technician skill.
03
PMP
Planned Maintenance Percentage
Share of maintenance hours that are scheduled rather than reactive. Plants above 85% PMP report MTBF 40–60% higher than reactive-dominant programs.
04
Schedule Compliance
PM Completion Rate
Percentage of scheduled preventive work completed on time. Chronic deferral here is the earliest leading indicator of a future corrective work spike.
05
OEE
Overall Equipment Effectiveness
Availability × Performance × Quality combined into one number. Moving a plant from 65% to 75% OEE can add millions in output with zero capital investment.
OxMaint calculates MTBF, MTTR, PMP, schedule compliance, and OEE automatically from every work order your team closes — no spreadsheets, no end-of-month reconciliation.
Where Does Your Plant Stand?
Reference ranges drawn from NERC GADS reliability data and power generation maintenance records
| KPI | At-Risk | Industry Average | Top Quartile |
|---|---|---|---|
| MTBF (hours) | Below 500 | 500 – 800 | Above 1,200 |
| MTTR (hours) | Above 14 | 8 – 14 | Below 6 |
| Planned Maintenance % | Below 60% | 60% – 80% | Above 85% |
| Schedule Compliance | Below 70% | 70% – 88% | Above 92% |
| OEE | Below 65% | 65% – 78% | Above 85% |
Expert Review
Renata Oduya — Reliability Engineering Consultant, 16 years in fossil and combined-cycle generation
Plants rarely fail a benchmark because the equipment is bad. They fail because nobody is watching the trend line until it's already a forced outage. The teams that consistently sit in the top quartile are not doing anything exotic — they are closing every work order with accurate timestamps and failure codes, so MTBF and MTTR calculate themselves correctly instead of being guessed at in a spreadsheet once a month. Get the data discipline right first; the KPI improvement follows almost automatically.
Frequently Asked Questions
What MTBF should our power plant be targeting?
Target depends on equipment age, design class, and duty cycle, but an MTBF below 800 hours generally signals a preventive maintenance gap rather than expected wear. Sign in to OxMaint to see your asset-level MTBF trend calculated automatically from existing work order history.
Why does our MTTR keep climbing even though technicians are skilled?
Rising MTTR is usually a parts and process problem, not a skills problem — delayed spare part staging, slow diagnosis, or unclear work order routing add hours before a wrench is even picked up. Book a demo to see how mobile work order routing and pre-staged spare kits reduce MTTR without adding headcount.
How is OEE different from simple uptime tracking?
Uptime only measures whether an asset is running; OEE multiplies availability by performance and quality, capturing slow starts, derated output, and quality losses that uptime alone hides. Most plants discover their real OEE is 10–15 points lower than their reported uptime. Start a free trial to see OEE broken down by contributing factor for every asset.
Can we benchmark against our own historical performance instead of industry averages?
Yes, and most reliability engineers use both — industry benchmarks set a general target, but unit-over-unit historical comparison within your own fleet reveals which assets and crews are genuinely improving. Book a demo to benchmark your specific asset fleet against both industry data and its own trend history.
OxMaint · Analytics & Reporting · Power Generation
Stop calculating MTBF and MTTR by hand once a month. See every reliability KPI updated live, the moment a work order closes.
