Maintenance and reliability intelligence
See where your maintenance money goes, and what it buys you.
Reliability Center connects to the CMMS you already run and turns years of work orders into a clear picture of maintenance spend, the cost of downtime, and whether preventive work is actually getting done. Leadership gets the business view. Reliability engineers get the analysis behind it.
Maintenance spend
$4.61M
On budget · ▼ 6% vs last year
Downtime cost
$1.37M
▼ 18% vs last year
PM completion
91%
Target 95%
Savings identified
$640k/yr
3 recommended actions
Top cost driversRepairs + downtime
Boiler feed pump P-101$312k
Conveyor C-12$248k
Chiller 2$176k
Press line 3$141k
Sample data
Connects to the CMMS you already run
IBM MaximoHxGN EAMFiixeMaintLimbleMaintainXUpKeepLLumin
Why it matters
Most plants are sitting on years of maintenance data they never use
Every work order your technicians close records what failed, when, and what it cost. Very little of it gets turned into decisions. Here is why.
01Data goes in, insight never comes out
Your CMMS is built to schedule and track work, not to analyze it. Years of history sit in tables that nobody has time to dig through.
02Preventive work is a guess
PMs get done on schedule, but are they preventing failures, or just consuming labor? Without analysis, nobody can say which tasks earn their keep.
03Leadership can't see the plant
Executives get anecdotes and lagging monthly reports instead of a clear, current view of asset health and where the money is going.
How it works
From raw work orders to clear decisions, automatically
No new system for your technicians to learn and no change to how work gets recorded. Reliability Center works from the data you already have.
Connect
Securely connect to your CMMS with read-only access. Your system of record stays exactly as it is.
Audit your data
A data health score, the metrics you can build today, and the fields that would unlock more. Then we clean and standardize it.
Analyze
Spend, downtime cost, PM completion and reliability analysis are calculated automatically and kept current.
See it anywhere
Dashboards and alerts on your desktop or phone, kept up to date as new work orders close.
Products
One platform. Pick what your plant needs.
Start with an audit, then add the views each role needs. Choose a product to see what it includes and try a live sample.
Where every customer starts
Know what your data can do before you build anything
Every engagement starts here: how healthy your data is, what you can build today, and which fields would unlock more.
reliability.centerData health score
78 / 100
▲ 9 since first audit
Metrics you can build
84 of 104
58 right away
CMMS modules in use
6 of 9
Meters, inspections, projects empty
Open questions
5 of 12
About your codes and settings
What's workingStrong or clearly improving
Labor by a named technician96%
WOs linked to a known asset97%
Completed WOs with labor hours91%
Line marks the 90% target
Where to focusGaps that limit what the data can tell you
Descriptive comments58%
Actual, not rounded, time44%
Closed one at a time72%
Key-field completeness79%
Line marks the target
Key findingsMost serious first
- Serious56% of technician labor entries are whole or half hoursHours look estimated, so time-based metrics are less reliable.
- Serious18% of work orders were closed in bulkTen or more closed in the same minute, so completion dates don't show when work finished.
- Warning20 of 104 metrics need information the CMMS doesn't record todayEach one names the field or source that would unlock it.
- Warning3 of 9 CMMS modules hold no dataMeters, inspections and projects are licensed but unused.
- GoodLabor logged by a named technician is up from 81% to 96%Almost every hour can now be tied to a person and a job.
Ready now
58
Your data supports them today
After a few answers
17
Once codes are confirmed
Lower confidence
9
A needed field is sparse
Can't build yet
20
14 not recorded, 6 need outside data
Metrics you can build, of 104 checkedSample metrics shown
- Ready now 58
- After a few answers 17
- Lower confidence 9
- Not recorded yet 14
- Needs outside data 6
Ready to buildBad-actor assets (Pareto)Downtime, cost and repeat failures by asset
Ready to buildPM compliance by due datePMs completed on time, by site and crew
Ready to buildMean time to repair (MTTR)From labor and completion times
Ready to buildReactive vs. proactive spendLabor and parts cost by work type
After open questionsPercent of planned workConfirm which work types count as planned
After open questionsOperational availabilityConfirm which status means the asset is down
Lower confidenceWeibull component lifeFailure cause filled on only 64% of failures
Lower confidenceCost of downtimeDowntime recorded on 71% of breakdowns
Not recorded yetMTBF by run hoursNeeds meter readings, not recorded today
Not recorded yetAsset criticality rankingCriticality field exists but is never filled
Needs outside dataOverall equipment effectivenessNeeds production counts from the line
Needs outside dataRecordable injury frequencyNeeds records from the safety system
Fields available
412
In the modules you use
Filled consistently
186
Ready for metrics
Sparse
61
Filled on some records
Never used
165
Exist but always empty
Field inventorySample fields shown
| Field | Module | Filled | Status |
|---|---|---|---|
| Asset | Work orders | 97% | Used |
| Work type | Work orders | 95% | Used |
| Failure mode | Work orders | 82% | Used |
| Failure cause | Work orders | 64% | Sparse |
| Downtime start and end | Work orders | 71% | Sparse |
| Labor comment | Labor | 58% | Sparse |
| Asset criticality | Assets | 0% | Never used |
| Meter reading | Meters | 0% | Never used |
Fields that would unlock the most metricsIf recorded consistently
| Field | Unlocks | For example |
|---|---|---|
| Failure cause | +11 | Cause Pareto, RCA tracking |
| Downtime start and end | +8 | Availability, cost of downtime |
| Asset criticality | +7 | Risk matrix, critical uptime |
| Run hours | +6 | MTBF by run time, Weibull |
| Labor comment, 10+ characters | +4 | Failure codes from repair text |
Checks run
9
On every work order and labor entry
Passing
4
No action needed
Need attention
5
Habits to fix
Contradicting records
1.2%
Closed before started
Consistency checksHow work is being recorded
| Check | Result | Status | Why it matters |
|---|---|---|---|
| Rounded hours | 56% whole or half hours | Fix | Estimates, not actual time |
| Short comments | 42% under 10 characters | Fix | No record of what was found and done |
| Bulk closing | 18% closed 10+ in a minute | Fix | Completion dates are unreliable |
| System-account labor | 6% of hours | Watch | Hours not tied to a person |
| Labor before the work order | 4% of entries | Watch | Records filled in after the fact |
| Closed before started | 1.2% of work orders | Pass | Dates contradict each other |
| Work orders without an asset | 3% | Pass | Work can't be traced to equipment |
Work orders, 12 months
6,240
▲ 4% vs prior year
People logging labor
23
Plus 1 system account
Modules in use
6 of 9
3 hold no data
Preventive share
52%
Target 60%
Work orders per monthAll work types
Work mixShare of work orders
Preventive52%
Corrective31%
Emergency9%
Project and other8%
CMMS modulesRecords, 12 months
| Module | Records | Status |
|---|---|---|
| Work orders | 6,240 | In use |
| Labor | 14,900 | In use |
| Preventive maintenance | 3,210 | In use |
| Parts | 2,130 | In use |
| Meters | 0 | No data |
| Inspections | 0 | No data |
Equipment families
12
Each with its own code set
Repair notes read
3,480
Technician comments
Codes suggested
146
Component, problem, cause, remedy
Awaiting your review
146
Nothing changes until you approve
Suggested failure codes: centrifugal pumpsBuilt from what technicians wrote about each repair
| Component | Problem | Cause | Remedy | Seen in |
|---|---|---|---|---|
| Mechanical seal | Leaking | Wear, dry running | Replace seal | 38 WOs |
| Bearing | Noise, vibration | Lubrication | Replace bearing | 27 WOs |
| Impeller | Low flow | Erosion | Replace impeller | 11 WOs |
| Coupling | Vibration | Misalignment | Realign | 9 WOs |
| Motor | Overheating | Overload | Inspect and reset | 7 WOs |
From repair text to codesExamples
| Technician wrote | Suggested code |
|---|---|
| “replaced leaking mech seal, shaft scored” | Mechanical seal / leaking / wear |
| “brg noisy, no grease in fitting” | Bearing / noise / lubrication |
| “coupling worn, realigned pump” | Coupling / vibration / misalignment |
Questions
12
About your codes and settings
Answered
7
Confirmed by your team
Open
5
Waiting on your answer
Metrics waiting
17
Unlock once answered
Questions for your teamWhat the data suggests, and our reading
| Question | What the data suggests | Status |
|---|---|---|
| Which work types count as planned work? | PM, PdM and project look planned; CM and EM unplanned | Open |
| Which asset status means “down”? | “DOWN” and “OOS” appear with downtime notes | Open |
| Who is the SYSTEM labor user? | Logs 6% of hours, mostly overnight | Open |
| Is BRKDWN emergency or corrective? | Used for urgent jobs started within the hour | Answered |
| Are priority 1 work orders safety related? | Most mention guards, leaks or lockout | Answered |
Sample audit and sample metrics shown · click the menu to explore each view
What you get
Every engagement starts with a data health audit of your CMMS. You'll see how healthy your records are, which metrics you can build today, and which fields, if your team starts using them, will unlock more.
- Data health scoreHow complete and trustworthy your records are, field by field.
- What you can build todayEvery metric in our library of 100+, marked ready, ready after a few answers, or blocked, with the reason.
- Fields that unlock moreThe handful of fields that would open up the most new metrics.
- Consistency checksRounded hours, bulk closing, one-word comments and records that contradict each other.
- Suggested failure codesA code set per equipment type, built from what technicians already write.
- A plan, not just a reportWe clean and standardize what you have, then build what your data supports.
For plant managers and executives
Know what maintenance is costing you, and whether the work is getting done
Where the money goes, what downtime costs, and whether preventive work is happening.
reliability.centerMaintenance spend
$4.61M
On budget · ▼ 6% vs last year
Downtime cost
$1.37M
▼ 18% vs last year
PM completion
91%
Target 95%
Savings identified
$640k/yr
3 recommended actions
Maintenance spend vs. budgetPlanned Reactive Budget
Reactive spend down 47% since OctoberPlanned share up from 58% to 76%
Top cost driversRepairs + downtime
Boiler feed pump P-101$312k
Conveyor C-12$248k
Chiller 2$176k
Press line 3$141k
Air compressor AC-4$96k
Are PMs getting done?Completion by area
Utilities97%
Warehouse93%
Packaging88%
Press shop76%
42 PMs overdue · backlog 3.1 weeks · line marks the 95% target
Spend, 12 months
$4.61M
0.9% over budget
Budget
$4.57M
3 sites
Planned spend
$3.00M
65% of total
Reactive spend
$1.61M
▼ 47% since Oct
Monthly spend vs. budgetTotal spend, $k
Dashed line: monthly budget $385k
Spend by siteActual vs. budget
| Site | Actual | Budget | Variance |
|---|---|---|---|
| North | $1.98M | $2.02M | 2% under |
| South | $1.71M | $1.58M | 8% over |
| East | $0.92M | $0.97M | 5% under |
Spend by category12 months
Labor$2.08M
Parts and materials$1.52M
Contractors$0.74M
Other$0.27M
Total maintenance cost
$4.61M
12 months, all sites
Labor
$2.08M
45% of total
Parts and materials
$1.52M
33% of total
Cost per work order
$739
6,240 work orders
Cost by type of workLabor, parts and contractors
Preventive$1.84M
Corrective$1.71M
Emergency$0.74M
Project and other$0.32M
Cost per work orderBy type of work
Preventive$567
Corrective$884
Emergency$1,317
Project and other$641
An emergency job costs 2.3 times a preventive one
What each asset costs to keep runningLabor plus parts, 12 months
| Asset | Labor | Parts | Total | vs. last year |
|---|---|---|---|---|
| Boiler feed pump P-101 | $118k | $96k | $214k | ▲ 38% |
| Conveyor C-12 | $92k | $71k | $163k | ▲ 12% |
| Chiller 2 | $64k | $58k | $122k | ▲ 9% |
| Press line 3 | $55k | $41k | $96k | ▼ 6% |
| Air compressor AC-4 | $38k | $29k | $67k | ▼ 11% |
Downtime cost
$1.37M
▼ 18% vs last year
Unplanned downtime
1,140 h
▼ 15% vs last year
Cost per hour
$1,200
Lost production + repairs
Downtime events
214
▼ 31 vs last year
Downtime cost by month$k
Downtime cost by area12 months
Boiler house$402k
Packaging$371k
Press shop$338k
Utilities$259k
Top causes12 months
Bearing failures$286k
Seal leaks$214k
Electrical faults$188k
Belt and chain wear$142k
PM completion
91%
Target 95%
PMs due, 12 months
4,820
Across 3 sites
Overdue now
42
▼ 18 vs last month
Backlog
3.1 weeks
Healthy range
PM completion trend% of PMs completed on time
Completion by areaLine marks the 95% target
Utilities97%
Warehouse93%
Packaging88%
Press shop76%
Overdue PMs by crewRight now
| Crew | Overdue | Oldest |
|---|---|---|
| Mechanical A | 17 | 23 days |
| Mechanical B | 11 | 15 days |
| Electrical | 9 | 12 days |
| Utilities | 5 | 6 days |
Critical assets
46
Ranked A by criticality
High-risk failure modes
12
RPN 200 or more
Critical asset availability
97.8%
Target 98%
Overdue safety work
2
Oldest 4 days
Criticality matrixFailure modes by severity and likelihood
4 modes in the red zone28 in amber
Top risksHighest risk priority numbers
| Asset | Failure mode | RPN | Action |
|---|---|---|---|
| P-101 | Seal leak | 288 | Seal redesign |
| Chiller 2 | Compressor trip | 240 | Add vibration monitoring |
| C-12 | Belt failure | 224 | Condition-based PM |
| Boiler B-1 | Tube leak | 210 | NDT inspection |
| AC-4 | Overheating | 168 | Clean coolers monthly |
Deferred maintenance
$1.2M
Work postponed past due
Past useful life
18%
Of critical assets
Replace candidates
5
Lifecycle cost rising
5-year capital need
$3.4M
Prioritized by risk
Replace or refurbishBased on lifecycle cost and failure trend
| Asset | Age | Repair cost trend | Recommendation |
|---|---|---|---|
| Air compressor AC-4 | 19 yrs | ▲ 42% / yr | Replace, FY27 |
| Chiller 2 | 16 yrs | ▲ 35% / yr | Replace, FY27 |
| Press line 3 hydraulics | 12 yrs | ▲ 18% / yr | Refurbish |
| Boiler feed pump P-101 | 9 yrs | ▲ 12% / yr | Fix root cause first |
| Conveyor C-12 | 7 yrs | Stable | Keep running |
Asset age profileCritical assets
Under 5 years22%
5 to 10 years40%
10 to 20 years20%
Over 20 years18%
Capital planRecommended spend by year
FY26$0.7M
FY27$1.7M
FY28$0.6M
FY29$0.4M
Savings identified
$640k/yr
3 recommended actions
Captured so far
$180k
Since April
In progress
2 actions
1 planned
Largest single action
$310k/yr
Reactive to planned
Recommended actionsEstimated savings per year
| Action | Saving | Effort | Status |
|---|---|---|---|
| Shift reactive work to planned | $310k | Medium | In progress |
| Fix the top 3 cost drivers | $220k | High | Planned |
| Change or retire low-value PMs | $110k | Low | In progress |
Cost drivers to fixEstimated saving per year
Boiler feed pump P-101: seal redesign$95k
Conveyor C-12: belt tracking$75k
Chiller 2: controls upgrade$50k
PM tasks to changeEstimated saving per year
| Task | Change | Saving |
|---|---|---|
| Belt inspection, conveyors | Condition-based | $48k |
| Visual check, compressors | Retire | $34k |
| Filter change, HVAC | Pressure-triggered | $28k |
Sites
3
North, South, East
Best performer
East
5% under budget, 96% PMs
Needs attention
South
8% over budget
Company PM completion
91%
Target 95%
Site scorecardLast 12 months
| Site | vs. budget | Downtime cost | PMs done | Planned work | Trend |
|---|---|---|---|---|---|
| North | 2% under | $520k | 91% | 62% | Improving |
| South | 8% over | $610k | 84% | 74% | Watch |
| East | 5% under | $240k | 96% | 83% | Improving |
Downtime cost by site12 months
South$610k
North$520k
East$240k
PM completion by siteLine marks the 95% target
East96%
North91%
South84%
ReportsGenerated automatically
| Report | Period | Audience | Status |
|---|---|---|---|
| Monthly maintenance review | September | Leadership | Ready |
| Executive summary | Q3 | Leadership | Ready |
| Site scorecard | September | Site managers | Ready |
| PM completion | Week 39 | Maintenance managers | Ready |
| Savings tracker | Q3 | Finance | Updating |
This month's headline findingsPlain-language summary
- Spend is on budget; reactive spend is down 47% since October.
- South is 8% over budget, driven by boiler feed pump P-101.
- Press shop PM completion (76%) is the main gap to the 95% target.
- $640k/yr of savings identified; $180k captured so far.
Sample data shown · click the menu to explore each view
What you get
The business view of your plants: where the money goes, what downtime costs, whether preventive work is happening, and where the next savings will come from.
- Spend vs. budgetBy site, area and asset, planned against reactive.
- Cost of downtimeA dollar figure on unplanned downtime, with the biggest drivers ranked.
- PM completion and backlogWhether preventive work is getting done, by site, area and crew.
- Savings opportunitiesWhere the next dollar of savings will come from, with an estimate.
- Risk and capital planningCriticality, deferred maintenance and replace-or-refurbish decisions.
- Site scorecards and benchmarksCompare plants on the same definitions, and against industry targets.
- Alerts and reportsTold when something changes; monthly reviews written for you.
- Total maintenance costLabor, parts and contractors, per asset and per work order.
North PlantTodaySpend vs budget
2% under
On track
Downtime cost
$520k
▼ 18% YoY
PMs done
91%
Target 95%
Savings found
$640k
per year
Boiler feed pump P-101$48k in repairs this quarter, 3× its budget. Repeat seal failures.
Downtime cost, last 8 weeks
On any phone
See how your plant is doing in seconds
Reliability Center installs to your home screen like an app. Open it and see spend against budget, the cost of downtime and whether PMs are getting done, with alerts when something needs your attention.
- Cost, downtime and PM completion for every site
- Alerts when an asset starts costing more than it should
- Tap any number to see the detail behind it
- Nothing to download from an app store
For reliability and maintenance engineers
The analysis behind the numbers, ready when you need it
Life data, reliability growth, failure analysis and PM optimization, from clean, standardized data.
reliability.centerAvailability
96.4%
▲ 1.8 pts vs last year
MTBF
41 days
▲ 22% vs last year
MTTR
3.2 h
▼ 0.6 h faster
Planned work
62%
Target 80%
Life data: Pump bearingsWeibull, 2-parameter
β = 2.4 wear-outB10 life 160 days90% confidence bounds
Reliability growth: Conveyor fleetCrow-AMSAA
Before β = 1.32 worseningAfter β = 0.71 improving
PM effectivenessFailures between PMs
| PM task | Assets | Fails | Verdict |
|---|---|---|---|
| Lubrication route | Conveyors | 0 | Effective |
| Vibration route | Pumps | 1 | Effective |
| Visual check | Compressors | 4 | Review |
| Filter change | HVAC | 6 | Review |
| Belt inspection | Conveyors | 9 | Change task |
Work mix and benchmarkPlanned vs. reactive
Planned work by site
North62%
South74%
East83%
Line marks the 80% target
Top 8 assets
54%
of plant downtime
Repeat failures
37
Same mode within 90 days
Bad actors flagged
8
▲ 2 this quarter
Worst MTBF
9 days
Boiler feed pump P-101
Downtime ParetoHours, last 12 months
Repeat failuresLast 90 days
| Asset | Failure mode | Count |
|---|---|---|
| Boiler feed pump P-101 | Mechanical seal leak | 3 |
| Conveyor C-12 | Belt misalignment | 3 |
| Air compressor AC-4 | Overheating | 2 |
| Pump P-204 | Bearing noise | 2 |
Top failure modesShare of failures
Bearing wear24%
Seal leakage18%
Misalignment13%
Electrical fault11%
Failures with a cause
64%
▲ 21 pts since coding review
Hidden failures
14%
Found by test or inspection
Common-cause events
6
Shared root cause
RCAs completed
9 of 11
2 in progress
Cause-of-failure ParetoShare of coded failures
Lubrication22%
Wear and age19%
Installation14%
Operating error11%
Design9%
FMEA from historyHighest risk priority numbers
| Failure mode | S | O | D | RPN |
|---|---|---|---|---|
| Pump seal leak | 8 | 6 | 6 | 288 |
| Compressor trip | 8 | 5 | 6 | 240 |
| Belt failure | 7 | 8 | 4 | 224 |
| Bearing seizure | 9 | 4 | 5 | 180 |
| Motor overheat | 6 | 4 | 5 | 120 |
Failure modes found in work order textSuggested codes from repair descriptions
| Repair text | Suggested code | Confidence |
|---|---|---|
| “replaced leaking mech seal, shaft scored” | Seal leakage | High |
| “belt tracking off, rubbing frame” | Misalignment | High |
| “tripped on high temp again” | Overheating | Medium |
Failure modes analyzed
14
Across 6 asset classes
Wear-out modes
6
Candidates for time-based tasks
Random modes
5
Candidates for condition monitoring
Infant mortality
3
Check installation quality
Life data: Pump bearingsWeibull, 2-parameter
β = 2.4 wear-outB10 life 160 days
Failure mode summaryWeibull results
| Failure mode | β | η | Pattern |
|---|---|---|---|
| Pump bearings | 2.4 | 410 d | Wear-out |
| Mechanical seals | 1.1 | 260 d | Random |
| Motor windings | 0.7 | 1,900 d | Infant mortality |
| Conveyor belts | 3.1 | 180 d | Wear-out |
Recommended strategy by modeFrom the life data
| Failure mode | Recommendation |
|---|---|
| Pump bearings | Replace before B10 life (160 days) |
| Mechanical seals | Vibration and leak monitoring |
| Motor windings | Review commissioning and installation checks |
| Conveyor belts | Scheduled replacement at 120 days |
Fleets tracked
6
Repairable systems
Improving
3
β below 1
Stable
2
β near 1
Worsening
1
Compressors
Reliability growth: Conveyor fleetCrow-AMSAA
Before β = 1.32After β = 0.71
Fleet growth summaryCrow-AMSAA β, last 12 months
| Fleet | β | Trend |
|---|---|---|
| Conveyors | 1.32 → 0.71 | Improving |
| Pumps | 0.86 | Improving |
| Chillers | 0.92 | Improving |
| Fans | 1.02 | Stable |
| Gearboxes | 0.98 | Stable |
| Compressors | 1.41 | Worsening |
Inherent availability
98.9%
Design capability
Operational availability
96.4%
▲ 1.8 pts vs last year
OEE, press line 3
71%
Target 80%
Down vs. degraded
62 / 38
% of asset-down events
Monthly availability of critical equipmentTarget 98%
OEE breakdown, press line 3Availability x performance x quality
Availability88%
Performance86%
Quality94%
OEE71%
MTBF and MTTR by asset classLast 12 months
| Asset class | MTBF | MTTR | Availability |
|---|---|---|---|
| Pumps | 62 d | 4.1 h | 99.7% |
| Conveyors | 28 d | 2.6 h | 99.6% |
| Compressors | 34 d | 6.8 h | 99.2% |
| Chillers | 51 d | 9.4 h | 99.2% |
PM tasks reviewed
312
North Plant
Effective
71%
No failures between PMs
Review
19%
Some failures between PMs
Change or retire
10%
$110k/yr saving
PM effectiveness by taskFailures between PMs, last 12 months
| PM task | Assets | Interval | Fails | Verdict |
|---|---|---|---|---|
| Lubrication route | Conveyors | Weekly | 0 | Effective |
| Vibration route | Pumps | Monthly | 1 | Effective |
| Thermography | Electrical panels | Quarterly | 0 | Effective |
| Visual check | Compressors | Weekly | 4 | Review |
| Filter change | HVAC | Monthly | 6 | Review |
| Belt inspection | Conveyors | Weekly | 9 | Change task |
Failures between PMs by asset classLast 12 months
Conveyors12
HVAC6
Compressors4
Pumps1
PM optimization signalsLast 12 months
PM find rate12%
PMs that never find anything38%
Condition-based share of PM22%
Failures within 14 days of a PM9%
PM interval longer than the failure interval on 7 tasks
Data health score
78 / 100
▲ 9 since first audit
Field completeness
87%
Key fields filled
Failure coding depth
64%
Mode and cause coded
WOs closed with notes
78%
Real comments, not “done”
Field completeness scorecardShare of work orders with the field filled
Asset97%
Work type95%
Downtime start and end71%
Failure mode82%
Failure cause64%
Actual labor hours88%
Fields that would unlock more metricsIf recorded consistently
| Field | Unlocks | Examples |
|---|---|---|
| Failure cause | +11 | Cause Pareto, RCA tracking |
| Downtime start and end | +8 | Availability, cost of downtime |
| Asset criticality | +7 | Risk matrix, critical uptime |
| Run hours | +6 | MTBF by run time, Weibull |
Metrics at target
2 of 6
North Plant
Biggest gap
Planned work
62% vs 80% target
Most improved
Reactive spend
▼ 47% since Oct
Peer comparison
3 sites
Same definitions
Benchmark comparisonPlant vs. typical best-practice targets
| Metric | North Plant | Target | Status |
|---|---|---|---|
| Planned work | 62% | 80% or more | Gap |
| PM completion | 91% | 95% or more | Close |
| Schedule compliance | 78% | 90% or more | Gap |
| Maintenance cost, % of asset value | 2.8% | 2% to 3% | On target |
| Overtime | 8% | 10% or less | On target |
| Reactive work | 38% | 20% or less | Gap |
Planned work by siteLine marks the 80% target
East83%
South74%
North62%
Failure rates vs. published industry dataFailures per million operating hours
| Equipment | Plant | Reference | Status |
|---|---|---|---|
| Centrifugal pumps | 182 | 140 | Above |
| Compressors | 410 | 360 | Slightly above |
| Electric motors | 38 | 44 | Within |
| Fans | 52 | 61 | Within |
Engineering reportsGenerated automatically
| Report | Scope | Status |
|---|---|---|
| Bad actor review | North Plant, September | Ready |
| Life data summary | Rotating equipment | Ready |
| Reliability growth | All fleets, Q3 | Ready |
| PM optimization | 312 tasks reviewed | Ready |
| Data quality | Failure coding gaps | Updating |
Data qualityHow complete the failure coding is
Failure mode coded82%
Cause coded64%
Downtime recorded91%
Asset linked97%
Sample data shown · click the menu to explore each view
What you get
Life data, reliability growth, failure analysis and PM optimization, calculated from clean, standardized data instead of spreadsheets.
- Bad actor identificationPareto by downtime, cost and frequency, with repeat failures flagged.
- Failure analysisCause Pareto and FMEA built from your own work order history.
- Life data analysisWeibull that handles censored data, with confidence bounds.
- Reliability growthCrow-AMSAA for repairable systems, before and after a fix.
- Availability and OEEInherent and operational availability, MTBF and MTTR by asset class.
- PM optimizationWhich tasks prevent failures, which never find anything, which to change.
- BenchmarksYour failure rates and ratios against published industry data.
- Data healthField completeness and coding depth, so you know what to trust.
For maintenance managers and their crews
Keep your technicians motivated to be the champions you want them to be
Know how your team does its work and uses the CMMS, and turn good habits into a friendly competition.
Tech Championship
North Plant · Q3 standings
- 2ndMRMarcus ReedElectrician92 pts2
- 1stADAna DelgadoMechanic93 pts1
- 3rdPSPriya ShahMechanic90 pts3
| # | Technician | Score | On time | PMs on time | Records | Actual time | vs Q2 |
|---|---|---|---|---|---|---|---|
| 1 | AD Ana DelgadoMechanic | 93 | 95% | ★98% | 90% | 88% | ▲ 3 |
| 2 | MR Marcus ReedElectrician | 92 | ★97% | 90% | 86% | ★93% | ▲ 1 |
| 3 | PS Priya ShahMechanic | 90 | 89% | 93% | ★94% | 84% | ▲ 6 |
| 4 | TB Tom BeckerMillwright | 84 | 88% | 86% | 80% | 82% | ▼ 2 |
| 5 | LO Luis OrtegaMechanic | 81 | 85% | 89% | 72% | 78% | ▲ 9 |
| 6 | SO Sam OkaforElectrician | 78 | 80% | 84% | 76% | 70% | ▲ 2 |
| 7 | JW Jen WalshHVAC technician | 76 | 78% | 81% | 70% | 74% | ▲ 4 |
- On-time finisherMarcus Reed · 97% of work orders by their due date
- PM championAna Delgado · 98% of PMs done on time
- Best documenterPriya Shah · 94% of entries with a real comment
- Time-keeperMarcus Reed · 93% actual, not rounded, hours
- Most improvedLuis Ortega · +9 points since Q2
- Rewards good work, never hours logged. On time 30%, PMs on time 25%, records 25%, actual time 20%.
- Fair comparisons. People are compared on similar work, and system accounts are left out.
- Built to motivate, not to police. Technicians see the leaders and their own standing.
- Everyone can win something. Awards in every category, plus most improved.
Sample data and names shown
What you get
Know how your team does its work and how they use the CMMS. The Tech Championship turns good habits into a friendly competition: work finished on time, PMs done when due, clear records and real labor hours. Better habits mean better data, and better data means better decisions.
- Tech ChampionshipScores on timeliness and record quality, never on hours logged.
- Awards for everyoneCategory winners and most improved, so everyone can win something.
- Technician trainingShort, site-specific lessons where the data shows a gap, built from your own failure history.
- Workload balanceA manager's view of hours and work orders per person.
- CMMS usage qualitySee who records real comments and actual time.
- Fair by designPeople are compared on similar work; technicians see the leaders and their own standing.
For storeroom and purchasing managers
Know what you'll need before the shelf is empty
Predicted demand, incoming purchase orders by promise date, and the stock you no longer need.
reliability.centerStock value
$1.86M
4,120 stocked parts
Parts at risk
14
Run out before resupply
Critical spares coverage
88%
Target 95%
Dead stock
$312k
17% of stock value
Parts that will run out before the next deliveryOn hand, predicted use and incoming POs by promise date
| Part | On hand | Need, 90 days | On order | PO promise date | Runs out | Status |
|---|---|---|---|---|---|---|
| Mechanical seal, P-101 | 1 | 3 | 2 | Nov 18 | Oct 29 | 20-day gap |
| Contactor, 40 A | 2 | 3 | 4 | Dec 5 (was Nov 10) | Nov 20 | PO slipped |
| Conveyor belt, 24 in | 1 | 2 | 1 | Oct 12 | Oct 9 | 3 days short |
| V-belt B68 | 6 | 9 | 0 | No PO | Nov 15 | Order by Oct 25 |
| Bearing 6312 | 4 | 6 | 10 | Oct 20 | Nov 2 | Covered |
Stock value by classWhat is on the shelf
Routine stock$710k
Critical spares$640k
Dead stock$312k
Slow-moving$198k
Critical spares coverageCritical assets with a spare on the shelf
Utilities96%
Press shop91%
Packaging84%
Boiler house80%
Line marks the 95% target
Parts forecast
412
With enough history
Driven by failures
61%
From failure rates
Driven by PMs
39%
From the PM schedule
Forecast accuracy
86%
Last quarter
Projected stock: mechanical seal, P-101Predicted use against incoming purchase orders
On hand 1Predicted use 3 in 90 daysSupplier lead time 6 weeksAction: expedite the PO or borrow from South
How demand is predictedWhat goes into each forecast
| Source | What it adds |
|---|---|
| Failure rates | Expected breakdown demand per part |
| PM schedule | Parts the planned work will use |
| Usage history | Seasonality and trends |
| Open POs | Incoming stock, by promise date |
| Lead times | When an order must be placed |
PM kit readinessParts for upcoming planned work
| Planned work | Starts | Parts |
|---|---|---|
| Conveyor PM, week 41 | Oct 6 | Ready |
| Chiller annual service | Oct 14 | 1 part short |
| Press line 3 overhaul | Oct 20 | Ready |
| Boiler inspection | Nov 3 | PO lands Nov 18 |
Open purchase orders
38
$214k on order
Late against promise
6
Promise date has passed
Promise dates slipped
4
Supplier moved the date
Average supplier delay
4.2 days
Last 12 months
Purchase orders against when the part is neededPromise date compared with the predicted run-out date
| PO | Part | Qty | Promise date | Needed by | Result |
|---|---|---|---|---|---|
| PO-4471 | Mechanical seal, P-101 | 2 | Nov 18 | Oct 29 | 20 days too late |
| PO-4455 | Contactor, 40 A | 4 | Dec 5 (was Nov 10) | Nov 20 | Slipped 25 days |
| PO-4482 | Conveyor belt, 24 in | 1 | Oct 12 | Oct 9 | 3 days too late |
| PO-4460 | Bearing 6312 | 10 | Oct 20 | Nov 2 | In time |
| PO-4466 | Hydraulic filter | 12 | Oct 28 | Dec 1 | In time |
Supplier delivery against promiseShare of POs delivered by the promise date
Supplier A94%
Supplier B81%
Supplier C68%
A supplier's track record adjusts how much its promise dates are trusted
Rush ordersPaid above the standard price
Standard orders$1.31M
Rush orders$210k
Rush premium paid: about $38k in 12 months
Dead stock
$312k
No use in 3 years
Slow-moving
$198k
One use in 2 years
Parts for retired assets
146
Nothing left to fit them to
Duplicate part numbers
83
Same part, two records
Largest dead stock linesValue on the shelf
| Part | Qty | Value | Last used | Fits |
|---|---|---|---|---|
| Gearbox, press line 1 | 1 | $46k | 2021 | Retired asset |
| Drive motor, 75 kW | 2 | $31k | 2022 | 1 asset left |
| PLC rack, legacy | 3 | $22k | 2020 | Retired asset |
| Pump casing, P-300 | 1 | $18k | 2022 | 1 asset left |
Why it is not movingShare of dead stock value
Asset retired41%
Over-ordered27%
Superseded part19%
Duplicate record13%
What to do with itRecommended action
Return or sell$128k
Transfer to another site$79k
Write off$71k
Keep as critical spare$34k
Manufacturers compared
64
Across 38 part types
Biggest life gap
2.1x
Bearings, Brand A vs. B
Parts worth switching
17
Shorter life, higher cost
Estimated saving
$58k/yr
From switching
Part life by manufacturerFrom your own replacement history
| Part type | Manufacturer | Average life | Cost per year | Verdict |
|---|---|---|---|---|
| Bearings, 6312 | Brand A | 26 months | $41 | Prefer |
| Bearings, 6312 | Brand B | 12 months | $73 | Avoid |
| Mechanical seals | Brand C | 14 months | $310 | Prefer |
| Mechanical seals | Brand D | 9 months | $420 | Review |
| V-belts | Brand E | 11 months | $38 | Prefer |
Claims identified
$84k
Last 12 months
Failures inside warranty
23
Replaced at your cost
Claims filed
9
14 still to file
Recovered so far
$31k
From 6 claims
Failures that happened inside the warranty periodParts replaced at your cost that may be claimable
| Part | Asset | Failed after | Warranty | Value | Claim |
|---|---|---|---|---|---|
| Drive motor, 30 kW | Conveyor C-12 | 7 months | 24 months | $9.4k | To file |
| Mechanical seal | Pump P-101 | 3 months | 12 months | $2.1k | Filed |
| VFD, 15 kW | Fan F-7 | 10 months | 18 months | $4.8k | To file |
| Compressor valve | AC-4 | 5 months | 12 months | $1.6k | Recovered |
Repeat defects by supplierSame part failing early, more than once
Supplier B7
Supplier C4
Supplier A1
Sample data shown · click the menu to explore each view
What you get
Most systems only tell you when a part drops below a fixed minimum. Reliability Center predicts what you will need from how your equipment actually fails and what your PM schedule calls for, counts incoming purchase orders by their promise dates, and tells you when the shelf will run empty before the next delivery.
- Predicted demandFrom failure rates and the PM schedule, not only past usage.
- PO promise dates built inIncoming orders are counted when they are promised, and flagged when that is too late.
- Critical spares coverageCritical assets with no spare on the shelf, against lead time.
- PM kit readinessWhether the parts for upcoming planned work are in stock.
- Dead and slow stockMoney tied up in parts that no longer move, and what to do with them.
- Supplier performanceDelivery against promise, rush-order premiums and price differences.
- Vendor and OEM scorecardsHow long each manufacturer's parts actually last in your plant.
- Warranty and supplier recoveryFailures inside the warranty period, and what you may be owed.
For plants with insurance, compliance or multi-site needs
Add what your plant needs, built on the same trusted data
Add-ons use the data the core platform has already cleaned and audited, so each one is a new view of work you have already done, not a new project.
Insurance-ready reliability report
A documented maintenance history and risk summary for your critical assets, ready to hand to your insurer.
- Maintenance history for critical assets
- Deferred maintenance and open risks
- The work orders behind every figure
Compliance evidence packs
Maintenance records and audit trails assembled for the programs you answer to, such as NFPA 70B, GMP and PSM.
- Records by asset and by program
- Completed and overdue work
- Export for auditors
Regulated equipment and safety work
Track the equipment and work orders that carry regulatory or safety weight.
- PM completion for cranes, pressure vessels and similar
- Safety work order response and aging
- Safety-critical equipment list
Process-safety early warning
Leading indicators from your safety-critical equipment, before an incident rather than after.
- Overdue work on safety-critical assets
- Repeat failures on protective devices
- Trends that need a second look
Multi-site portfolio
Every plant in one view, with what one site learns shared with the rest.
- Site triage and league table
- A fix at one site suggested to others
- Spares pooling across sites
M&A and valuation dossier
A reliability and deferred-maintenance picture of a plant, for diligence or valuation.
- Asset condition and age profile
- Deferred maintenance in dollars
- Reliability trends and risks
Compliance evidence, sampleNorth Plant · this quarter
| Program | Tasks done | Overdue | Evidence pack |
|---|---|---|---|
| Electrical maintenance (NFPA 70B) | 96% | 3 | Ready |
| Cranes and hoists | 100% | 0 | Ready |
| Pressure vessels | 92% | 2 | 2 items open |
| Calibration (GMP) | 98% | 1 | Ready |
| Safety work orders | 94% | 2 | Oldest 4 days |
Add-ons help you document and evidence your maintenance program. They are not a certification of compliance. Sample data shown.
For companies running more than one system
Many systems, one view
Maintenance lives in one system, money in another, production in a third. The questions leadership asks fall between them. We connect the systems you already run and answer those questions in one place.
CMMS / EAMERP and financeProduction / MESSensors and historiansSpreadsheets
reliability.centerOne standard model of your assets, work and costOne viewCost, downtime and reliability togetherOne set of numbersThe same definitions at every siteOne place to askDashboards and reports for every role
Questions it answers
- What did downtime really cost?Lost production and repair cost from finance data, not estimates.
- Work done vs. money spentWhat maintenance recorded against what finance paid. The gap is found money.
- Which failures cost production?Separate the failures that stopped output from the ones the line absorbed.
- What is our spares stock worth?Stock on hand against real valuation, slow movers and dead stock.
- True cost by vendorFailure rates against actual purchase prices and contracts.
- Replace or keep, in real dollarsAsset condition against book value and depreciation.
How a custom build works
- DiscoverWe map your systems and the questions that matter.
- ConnectRead-only connections to each source.
- BuildDashboards and reports shaped around your decisions.
- SupportWe keep it running as your systems change.
Custom work stays anchored to maintenance, reliability and cost questions, and pulls only the data those questions need.
Built by reliability engineers
Grounded in the standards your team already uses
Reliability Center is built by people who have done this work on the plant floor. The analysis follows established reliability and maintenance standards, so results hold up in front of auditors, engineers and leadership.
ISO 14224
EN 13306
IEC 60812
Weibull analysis
Crow-AMSAA
Security by design
- Your data stays yours. Each customer's data is isolated from every other customer's.
- Read-only access. We never write to or change your CMMS.
- Audited infrastructure. Hosted on independently audited cloud providers.
FAQ
Common questions
Which CMMS platforms do you connect to?
Reliability Center connects through each platform's published API, including IBM Maximo, HxGN EAM, Fiix, eMaint, Limble, MaintainX, UpKeep and LLumin. Some vendors include API access only on their enterprise plans. Running something else? Tell us, and we'll review your system's API.
Can it produce reports for our insurer or auditor?
Yes. Enterprise add-ons assemble an insurance-ready reliability report and compliance evidence packs for programs such as NFPA 70B, GMP and PSM, with the work orders behind every figure. They help you document your program; they are not a certification of compliance.
We run several systems. Can you bring them together?
Yes. Through custom development we connect your CMMS with finance, production and other systems, so cost, downtime and reliability sit in one view. We keep it focused on maintenance, reliability and cost questions.
Do we have to replace our CMMS?
No. Reliability Center works alongside the CMMS you already run. Your technicians keep working exactly as they do today.
Will it change anything in our system?
No. Reliability Center only reads your maintenance data. It never writes back to your CMMS.
Our data is messy. Is that a problem?
That is normal, and it is exactly what Reliability Center is built for. Cleaning and standardizing the data is part of the service, and data-quality scoring shows where better recording would pay off.
Do we need a reliability engineer on staff?
No. The analysis is built in and explained in plain language. If you do have reliability engineers, it gives them clean data and saves them hours of preparation.
Is there a mobile app?
Yes. Reliability Center works on any phone and can be added to your home screen like an app, so leaders can check plant performance in seconds.
How do we get started?
Request a demo. We'll walk you through Reliability Center, talk through your sites and your CMMS, and agree on a plan to connect your data.
Put your maintenance data to work
See Reliability Center in action. Tell us about your sites and your CMMS, and we'll set up a walkthrough built around your equipment.
- A walkthrough of the dashboards, shaped by your questions
- What a data health audit of your CMMS would cover
- Which products fit your plant, and which don't
Prefer email? info@reliability.center
Thanks, your request is in.
We'll reply by email to set up a time.