Maintenance KPIs

Plain-English Definition#

Maintenance Key Performance Indicators (KPIs) are measurable values used to evaluate the effectiveness, efficiency, reliability, and overall performance of a maintenance organization.

KPIs provide objective evidence of how well maintenance processes support safety, asset reliability, production, workforce development, and financial performance.

Well-designed KPIs help leaders make informed decisions, identify improvement opportunities, and measure progress toward strategic goals.

Executive Summary#

Maintenance organizations generate enormous amounts of data.

KPIs transform that data into meaningful information that supports decision-making.

Effective KPI systems help organizations:

• Measure maintenance performance
• Improve equipment reliability
• Increase planned work
• Reduce emergency maintenance
• Optimize maintenance costs
• Improve workforce performance
• Support continuous improvement
• Align maintenance with business objectives

Organizations should measure performance to improve decisions—not simply to create reports.

Why Maintenance KPIs Matter#

Without objective measurements, maintenance leaders rely on assumptions and opinions.

Common consequences include:

• Conflicting priorities
• Poor resource allocation
• Ineffective improvement efforts
• Limited accountability
• Difficulty demonstrating maintenance value
• Inconsistent decision-making

KPIs provide visibility into organizational performance and guide continuous improvement.

What Maintenance KPIs Are#

Maintenance KPIs include measurements related to:

• Reliability
• Planning and Scheduling
• Work Management
• Workforce Performance
• Materials Management
• Financial Performance
• Safety
• Continuous Improvement

KPIs should provide actionable information rather than simply reporting activity.

What Maintenance KPIs Are Not#

Maintenance KPIs are not:

• Numbers collected without purpose
• Reports that nobody reviews
• Targets that encourage undesirable behavior
• Measurements used only for employee discipline
• Every metric available within the CMMS

Every KPI should support a specific business decision.

Objectives#

An effective KPI program should:

• Support strategic objectives
• Improve maintenance decision-making
• Increase accountability
• Identify trends
• Prioritize improvement efforts
• Measure process performance
• Demonstrate maintenance value
• Encourage continuous improvement
• Align departments around common goals

KPI Philosophy#

The purpose of measurement is improvement.

Organizations should collect only the information necessary to understand performance and guide decisions.

A small number of meaningful KPIs is more valuable than a large collection of rarely reviewed reports.

Characteristics of Effective KPIs#

High-quality KPIs are:

• Clearly defined
• Easy to understand
• Consistently calculated
• Timely
• Actionable
• Relevant to business objectives
• Based on reliable data
• Reviewed regularly

If a KPI does not influence decisions, it should be reconsidered.

KPI Hierarchy#

Maintenance KPIs should exist at multiple organizational levels.

Strategic KPIs

Measure long-term business outcomes.

Examples:

• Asset Availability
• Maintenance Cost
• Overall Equipment Effectiveness (OEE)

Tactical KPIs

Measure departmental performance.

Examples:

• Planned Work Percentage
• PM Compliance
• Schedule Compliance
• Inventory Accuracy

Operational KPIs

Measure daily execution.

Examples:

• Work Orders Completed
• Emergency Work
• Schedule Attainment
• Planner Backlog

Each level should support the level above it.

Relationship to Maintenance Leadership#

Maintenance leaders define organizational goals.

KPIs measure progress toward those goals.

Well-designed KPIs strengthen accountability while supporting better decision-making throughout the organization.

Inputs#

Maintenance KPIs rely on information from:

• CMMS
• ERP systems
• Financial systems
• Production systems
• Reliability analyses
• Safety reports
• Inventory systems
• Workforce development records

Outputs#

An effective KPI program produces:

• Executive dashboards
• Department scorecards
• Trend analysis
• Improvement priorities
• Resource allocation decisions
• Business insights
• Continuous improvement opportunities

Reliability KPIs#

Reliability KPIs measure how consistently equipment performs its intended function.

Common reliability KPIs include:

• Mean Time Between Failures (MTBF)
• Mean Time To Repair (MTTR)
• Asset Availability
• Overall Equipment Effectiveness (OEE)
• Repeat Failure Rate
• Bad Actor Count
• Defect Elimination Rate

Reliability KPIs should focus on long-term asset performance rather than short-term repair activity.

Planning and Scheduling KPIs#

Planning and Scheduling KPIs evaluate how effectively work is prepared and executed.

Recommended KPIs include:

• Planned Work Percentage
• Schedule Compliance
• Schedule Attainment
• Planning Backlog Age
• Planning Accuracy
• Work Package Completeness
• Wrench Time

Organizations should trend planned-work and schedule-compliance measures against governed local targets and investigate sustained adverse movement.

Work Management KPIs#

Work Management KPIs evaluate the effectiveness of the maintenance workflow.

Examples include:

• Work Orders Created
• Work Orders Closed
• Average Work Order Age
• Backlog Size
• Backlog Age
• Work Request Response Time
• Emergency Work Percentage

These KPIs identify bottlenecks and workflow inefficiencies.

Preventive Maintenance KPIs#

Preventive Maintenance KPIs evaluate the health of the PM program.

Recommended measurements include:

• PM Compliance
• PM Completion Quality
• PM Schedule Adherence
• PM Effectiveness
• PM-Induced Failure Rate
• PM Labor Hours
• PM Cost

High PM compliance alone does not guarantee an effective PM program.

Quality is as important as completion.

Workforce KPIs#

Workforce KPIs measure organizational capability.

Examples include:

• Employee Turnover
• Training Hours
• Competency Growth
• Internal Promotion Rate
• Overtime Percentage
• Employee Engagement
• Safety Participation

These KPIs help leaders understand workforce health beyond staffing levels.

Materials Management KPIs#

Materials KPIs evaluate inventory performance and support for maintenance execution.

Recommended KPIs include:

• Inventory Accuracy
• Inventory Turns
• Stockout Rate
• Material Readiness
• Emergency Purchases
• Obsolete Inventory
• Supplier On-Time Delivery
• Inventory Carrying Cost

Materials KPIs should support maintenance execution rather than inventory reduction alone.

Financial KPIs#

Financial KPIs evaluate maintenance's contribution to business performance.

Common financial KPIs include:

• Maintenance Cost
• Maintenance Cost as a Percent of RAV
• Cost per Work Order
• Maintenance Labor Utilization
• Contractor Spending
• Inventory Value
• Maintenance Cost Avoidance

Financial KPIs should balance cost control with long-term asset reliability.

KPI Relationships#

Individual KPIs should never be interpreted in isolation.

For example:

• Rising Planned Work Percentage may accompany lower Emergency Work Percentage.
• Improved Planning Quality may support higher Schedule Compliance.
• Better Material Readiness may support higher Wrench Time.
• Improved Workforce Competency may contribute to fewer Repeat Failures.

Understanding relationships prevents misleading conclusions.

Controlled Maintenance KPI Definitions#

These definitions are the canonical maintenance-process calculations for this library. Sites may add local dimensions, but they should not change the numerator, denominator, timing rule, or exclusions without documented governance approval.

PM Compliance#

• Definition: Percentage of preventive maintenance work due in the reporting period that was completed by its governed due date.
• Formula: `PM compliance (%) = PM work orders completed by due date / PM work orders due × 100`
• Unit and period: Percent, normally weekly and monthly.
• Data sources: CMMS work-order type, governed due date, completion timestamp, cancellation reason, and asset status.
• Owner: Maintenance planning owner; CMMS data steward verifies source-field quality.
• Include: Active PM work orders whose governed due date falls inside the period.
• Exclude: Approved deletions, duplicate work orders, and work canceled because the asset was formally retired before the due date.
• Assumptions and limits: Completion means required work and closeout evidence are complete. This metric does not prove PM quality or effectiveness.
• Control and gaming risk: Lock due dates after schedule freeze; audit late date changes, mass closures, and cancellation codes.
• Example: 92 of 100 governed PM work orders were completed by their due dates: `92 / 100 × 100 = 92%`.

Schedule Compliance#

• Definition: Percentage of work orders on the frozen weekly schedule that were completed within that schedule window.
• Formula: `Schedule compliance (%) = scheduled work orders completed in window / work orders on frozen schedule × 100`
• Unit and period: Percent, weekly.
• Data sources: Frozen schedule snapshot, work-order completion timestamp, approved break-in record, and schedule-change log.
• Owner: Maintenance scheduling owner; maintenance supervisor confirms execution status.
• Include: Every work order committed at schedule freeze.
• Exclude: Only formally approved removals caused by documented operational constraints; report emergency break-in work separately.
• Assumptions and limits: A completed work order must meet closeout requirements. Equal work-order weighting can hide labor-hour variance, so labor-hour schedule attainment may be shown as a companion metric.
• Control and gaming risk: Preserve immutable schedule snapshots; prohibit retroactive schedule removal and incomplete administrative closure.
• Example: 42 of 48 frozen-schedule work orders were completed in the week: `42 / 48 × 100 = 87.5%`.

Emergency Work Percentage#

• Definition: Share of total maintenance labor hours consumed by work that met the governed emergency definition at initiation.
• Formula: `Emergency work (%) = emergency maintenance labor hours / total maintenance labor hours × 100`
• Unit and period: Percent, weekly and monthly.
• Data sources: Work-order priority at creation, emergency approval, booked labor hours, and total maintenance labor hours.
• Owner: Maintenance manager; work-management process owner audits priority use.
• Include: Labor booked to work classified as an emergency under the approved priority standard.
• Exclude: Planned overtime, routine urgent work, projects, and work reclassified after execution without documented approval.
• Assumptions and limits: Labor hours measure resource consumption, not production consequence or risk severity.
• Control and gaming risk: Require emergency approval and reason code; audit priority downgrades, missing labor bookings, and emergency work hidden in standing work orders.
• Example: 36 emergency hours out of 720 total maintenance hours: `36 / 720 × 100 = 5%`.

Maintenance Cost as a Percentage of RAV#

• Definition: Annual maintenance cost divided by governed replacement asset value (RAV).
• Formula: `Maintenance cost as % of RAV = annual included maintenance cost / governed RAV × 100`
• Unit and period: Percent, trailing twelve months or fiscal year.
• Data sources: General ledger, maintenance cost centers, contractor and material transactions, asset register, and approved RAV valuation record.
• Owner: Maintenance manager and finance owner jointly approve the cost boundary; asset management owns RAV governance.
• Include: Defined maintenance labor, materials, services, and contractor costs for assets included in the RAV base.
• Exclude: Expansion capital, unrelated operations cost, and assets outside the governed RAV population. Treatment of major overhauls must be stated and applied consistently.
• Assumptions and limits: RAV method, currency date, inflation basis, and asset population must be disclosed. Cross-company comparison is unreliable when boundaries differ.
• Control and gaming risk: Reconcile cost centers and asset population annually; prevent shifting maintenance expense to projects or using stale RAV.
• Example: `$1.8 million / $120 million × 100 = 1.5%`.

Mean Time Between Failures (MTBF)#

• Definition: Average operating time between functional failures of a repairable asset within a defined boundary.
• Formula: `MTBF = total operating time / number of failures`
• Unit and period: Hours (or days) per failure; calculated over a rolling period, normally trended over 12 months to smooth low failure counts.
• Data sources: CMMS failure-coded corrective work orders and asset runtime or operating-hours log.
• Owner: Reliability engineer; maintenance planner verifies failure coding.
• Include: Unplanned corrective work orders coded as a functional failure on the defined asset boundary.
• Exclude: Planned/preventive maintenance downtime, standby or idle time not counted as operating time, and failures on components outside the defined asset boundary.
• Assumptions and limits: The arithmetic estimate requires a stable asset boundary and consistent operating-time and failure definitions. Using MTBF as a stable reliability estimate or forecast also requires comparable operating context and roughly stable failure behavior; wear-out, infant-mortality patterns, and small failure counts limit interpretation. MTBF is not a prediction of when the next failure will occur, and it is not a warranty or replacement interval.
• Control and gaming risk: Standardize the failure-code taxonomy and audit reclassification of failures as "planned" or "cause unknown" to avoid inflating MTBF; require mandatory operating-hours capture.
• Example: An asset runs 4,000 operating hours in a quarter with 4 coded failures: `4,000 / 4 = 1,000 hours`.

Mean Time To Repair (MTTR)#

• Definition: Average active hands-on repair time required to restore a failed asset to function, measured from repair start to functional verification.
• Formula: `MTTR = total active repair time / number of repair events`
• Unit and period: Hours per repair; calculated monthly.
• Data sources: CMMS work-order timestamps for active repair start and functional-restoration confirmation.
• Owner: Maintenance supervisor; planner verifies timestamp quality.
• Include: Active hands-on repair time from work start to verified functional restoration.
• Exclude: Wait time for parts, approvals, or access, and administrative closeout time — track these separately as delay categories rather than folding them into MTTR.
• Assumptions and limits: Assumes accurate start/stop timestamps for active repair. Rare, very long repairs can skew the average; report outliers separately. MTTR alone does not capture total downtime experienced by operations — see delay/logistics metrics for that.
• Control and gaming risk: Define "repair start" and "repair complete" precisely; audit paused or stopped work-order clocks and the practice of splitting one long repair into multiple work orders to lower the reported average.
• Example: 4 repairs in a quarter with 20 total active-repair hours: `20 / 4 = 5 hours`.

Overall Equipment Effectiveness (OEE)#

• Definition: Composite measure of how effectively an asset or line performs during planned production time, combining availability, performance, and quality losses.
• Formula: `OEE = Availability × Performance × Quality`, where `Availability = run time / planned production time`, `Performance = (ideal cycle time × total count) / run time`, and `Quality = good count / total count`.
• Unit and period: Percent; calculated per shift or day, reviewed as a weekly or monthly trend.
• Data sources: Production/MES run data, CMMS downtime-reason codes, and quality or scrap records.
• Owner: Production or operations manager, jointly with the reliability engineer.
• Include: Only scheduled production time as planned production time; downtime coded to defined loss categories (breakdown, changeover, minor stop, speed loss, defect/rework).
• Exclude: Time the asset is not scheduled to run (no demand, planned shutdown) from planned production time — this is not counted as a loss.
• Assumptions and limits: Assumes an accurate, currently valid ideal/rated cycle time and consistent downtime and quality coding. OEE is asset- and line-specific; a single universal "world-class" benchmark does not apply uniformly across dissimilar assets and duty cycles.
• Control and gaming risk: Lock and govern the ideal-cycle-time reference value; audit reclassification of scheduled downtime as unscheduled, and under-reporting of scrap/rework, both of which artificially inflate OEE.
• Example: Planned production time 480 minutes, run time 420 minutes (Availability 87.5%); ideal cycle time 1 minute/unit, 350 units produced (Performance 83.3%); 330 good units of 350 (Quality 94.3%): `0.875 × 0.833 × 0.943 ≈ 68.7%`.

Wrench Time#

• Definition: Share of a maintenance technician's available paid work time spent on direct, hands-on maintenance work, as distinct from travel, waiting, or administrative time. A work-management system efficiency indicator, not an individual productivity score.
• Formula: `Wrench time (%) = direct hands-on maintenance time / total observed paid work time in the defined study scope × 100`
• Unit and period: Percent; measured through a periodic sampling study or structured observation, not continuous individual monitoring.
• Data sources: Work-sampling studies, structured direct observation, or time-tracking/CMMS labor logs.
• Owner: Maintenance manager or planner, with workforce representative involvement in study methodology.
• Include: Count only direct, hands-on maintenance activity in the numerator. Keep travel, waiting for parts/permits/access, briefings, paperwork, and other sampled in-scope paid time in the denominator and track them as separate cause-coded categories.
• Exclude: Approved breaks, leave, and time outside the defined observation population from both numerator and denominator. Document any treatment of training before comparison across periods.
• Assumptions and limits: Assumes a statistically representative, unbiased sampling method. Short or point-in-time studies can be unrepresentative. Wrench time reflects planning, parts availability, and scheduling quality — a system-level indicator, not a measure of individual worker effort.
• Control and gaming risk: Document and hold the sampling methodology constant; do not use wrench time as an individual performance metric or disciplinary tool, which damages trust and can pressure technicians to skip safety or planning steps to inflate tool-time; watch for behavior change limited to observed sampling windows.
• Example: An 8-hour (480-minute) shift with 216 minutes of observed direct hands-on repair time: `216 / 480 × 100 = 45%`.

Selecting the Right KPIs#

Organizations should select KPIs based on:

• Business objectives
• Organizational maturity
• Asset criticality
• Available data quality
• Decision-making needs

Collecting unnecessary metrics increases reporting effort without improving performance.

KPI Ownership#

Every KPI should have:

• A clear definition
• A documented calculation
• A responsible owner
• A review frequency
• A target value
• Defined improvement actions

Ownership ensures KPIs remain useful rather than becoming static reports.

Leading and Lagging Indicators#

A balanced KPI program includes both leading and lagging indicators.

Leading indicators measure activities that influence future performance.

Examples include:

• Planned Work Percentage
• PM Compliance
• Schedule Compliance
• Training Hours
• Material Readiness
• Planning Backlog Health

Lagging indicators measure outcomes that have already occurred.

Examples include:

• MTBF
• MTTR
• Equipment Availability
• Emergency Work Percentage
• Maintenance Cost
• Repeat Failure Rate

Mature KPI programs use leading indicators to guide action and lagging indicators to assess results.

Building Effective Dashboards#

Dashboards should present only the information needed to make decisions.

An effective dashboard should:

• Highlight trends
• Show targets
• Identify exceptions
• Support drill-down analysis
• Be updated consistently
• Be easy to interpret

Avoid overcrowding dashboards with excessive metrics.

Executive Scorecards#

Executive scorecards should summarize maintenance performance at a strategic level.

Recommended executive KPIs include:

• Asset Availability
• OEE
• Maintenance Cost as % of RAV
• Planned Work Percentage
• Emergency Work Percentage
• Safety Performance
• Inventory Accuracy
• Workforce Turnover

Executives should focus on business outcomes rather than operational detail.

Department Scorecards#

Maintenance managers require greater operational detail.

Typical department scorecards include:

• Schedule Compliance
• PM Compliance
• Backlog Age
• Wrench Time
• MTBF
• MTTR
• Inventory Turns
• Training Progress

Department scorecards should guide weekly and monthly improvement efforts.

Benchmarking#

Benchmarking compares organizational performance over time or against peer organizations.

Useful benchmarking sources include:

• Historical internal performance
• Multiple facilities within the company
• Industry associations
• Reliability studies
• SMRP benchmarking data

Benchmarking should identify improvement opportunities rather than assign blame.

KPI Review Cadence#

KPIs should be reviewed at the appropriate frequency.

Daily

• Schedule attainment
• Emergency work
• Safety observations

Weekly

• Schedule compliance
• Planned work
• Backlog health
• Material readiness

Monthly

• MTBF
• MTTR
• PM compliance
• Inventory performance
• Financial performance

Quarterly

• Workforce development
• Strategic objectives
• Capital effectiveness

Common KPI Mistakes#

Organizations frequently:

• Measure too many KPIs.
• Use inconsistent calculations.
• Reward the wrong behaviors.
• Ignore data quality.
• Review reports without action.
• Focus only on lagging indicators.
• Compare unrelated facilities without context.
• Change definitions over time.

Good KPIs encourage better decisions—not better reporting.

Case Study#

The following is an illustrative composite drawn from common patterns across maintenance organizations, not a specific documented case.

A manufacturing facility tracked more than 120 maintenance metrics but reviewed only a handful consistently.

Leadership redesigned the KPI system by:

• Reducing the number of KPIs
• Standardizing definitions
• Assigning KPI owners
• Creating weekly scorecards
• Linking metrics to improvement actions

Within one year:

• Reporting time decreased.
• Decision quality improved.
• Planned work increased.
• Emergency work declined.
• Reliability performance improved.

The improvement resulted from better KPI governance rather than additional reporting.

Continuous Improvement#

KPI programs should evolve as business objectives change.

Organizations should routinely evaluate:

• KPI relevance
• Data quality
• Reporting efficiency
• Dashboard usability
• Improvement effectiveness

Metrics should continuously support better operational decisions.

Knowledge Graph Updates#

Future Knowledge Library topics introduced:

• KPI Dashboards
• Leading Indicators
• Lagging Indicators
• Scorecards
• Benchmarking
• Data Governance
• Performance Reviews
• Executive Reporting
• Maintenance Analytics
• KPI Definitions
• Reliability Dashboards
• Executive Scorecards
• Metric Ownership
• Data Quality
• Performance Analytics
• KPI Governance
• Maintenance Benchmarking
• Dashboard Design
• Department Scorecards
• Data Visualization
• Continuous Improvement Metrics

Industry Applications#

Food Manufacturing#

Maintenance KPIs should emphasize:

• Food safety support
• Asset availability
• PM compliance
• Emergency work
• Refrigeration reliability
• Schedule compliance

Distribution and Warehousing#

Recommended KPIs include:

• Conveyor availability
• Forklift uptime
• Battery system reliability
• Material readiness
• Backlog age
• Labor utilization

Municipal Utilities#

Utility organizations should monitor:

• Service availability
• Regulatory compliance
• PM completion
• Critical asset reliability
• Emergency response time
• Infrastructure backlog

Commercial Facilities#

Typical KPIs include:

• HVAC availability
• Work order response time
• PM compliance
• Energy-related maintenance
• Occupant comfort complaints
• Contractor performance

Small Manufacturing#

Smaller organizations should begin with a focused KPI set:

• Planned Work Percentage
• Emergency Work Percentage
• PM Compliance
• MTBF
• Backlog Age
• Inventory Accuracy
• Maintenance Cost
• Safety Performance

Start with a few actionable KPIs and expand only as reporting maturity increases.

Maintenance KPIs for Small Business Owners#

Small businesses rarely need complex dashboards.

Review monthly:

• Equipment breakdowns
• Maintenance spending
• PM completion
• Critical spare availability
• Downtime
• Safety incidents

Simple, consistently reviewed metrics are more valuable than extensive reports.

KPI Maturity Model#

Level 1 — Reactive#

• Little or no KPI reporting
• Decisions based on opinion
• Inconsistent data

Level 2 — Developing#

• Basic KPI dashboard
• Manual reporting
• Limited trend analysis

Level 3 — Managed#

• Standard KPI definitions
• Routine reviews
• Department scorecards
• Improvement actions tracked

Level 4 — Optimized#

• Enterprise dashboards
• Predictive analytics
• Automated reporting
• KPI-driven decision making
• Continuous improvement culture

KPI Implementation Roadmap#

Step 1 Define business objectives.

Step 2 Select a limited set of meaningful KPIs.

Step 3 Document definitions and formulas.

Step 4 Verify data quality.

Step 5 Assign KPI ownership.

Step 6 Build dashboards and scorecards.

Step 7 Establish review cadence.

Step 8 Link every KPI to improvement actions.

Step 9 Review and refine regularly.

Common Targets and Benchmark Guidance#

Targets should reflect business objectives and asset criticality rather than arbitrary industry averages.

Examples include:

• Planned Work Percentage — Increasing trend
• Emergency Work Percentage — Decreasing trend
• PM Compliance — High and consistent
• Inventory Accuracy — High and improving
• Schedule Compliance — Consistently achieved
• Employee Turnover — Stable or decreasing

Focus on sustained improvement over time rather than chasing isolated benchmark values.

Best Practices#

• Measure only what influences decisions.
• Standardize KPI definitions.
• Balance leading and lagging indicators.
• Review KPIs on a defined cadence.
• Investigate trends rather than isolated values.
• Assign clear ownership.
• Connect every KPI to an improvement plan.
• Continuously improve dashboard quality.

Product Opportunities#

The items below are potential future product ideas for roadmap and planning purposes. They are not existing Reliability Method products, features, or services.

Templates#

• KPI Dictionary
• Executive Scorecard
• Department Dashboard
• Monthly KPI Review Agenda
• KPI Action Tracker
• Benchmark Worksheet

Calculators#

• MTBF Calculator
• MTTR Calculator
• Planned Work Calculator
• Inventory Turn Calculator
• Maintenance Cost % RAV Calculator
• OEE Calculator

AI Tools#

• KPI Advisor
• Dashboard Analyzer
• Trend Detection Assistant
• Benchmark Comparison Assistant
• Corrective Action Recommender

Facility Manager Features#

• Executive Dashboard
• Department Scorecards
• KPI Trend Analysis
• Automated Alerts
• Benchmark Tracking
• AI Performance Insights

Training#

• Maintenance KPI Fundamentals
• Dashboard Design
• Data-Driven Maintenance Management
• Benchmarking
• Performance Improvement

Consulting#

• KPI Assessments
• Dashboard Development
• Maintenance Performance Reviews
• Executive Reporting Systems
• Maintenance Analytics Programs

Related Knowledge Topics#

• Maintenance Leadership
• Building a Maintenance Department
• Maintenance Planning
• Maintenance Scheduling
• Work Order Management
• Backlog Management
• Reliability Engineering
• Materials Management
• CMMS Fundamentals

References#

• SMRP Body of Knowledge
• ISO 55000 — Asset Management
• ISO 14224 — Reliability and Maintenance Data
• Society for Maintenance & Reliability Professionals publications
• Reliability Method Internal Standards

Revision History#

Version 1.0 Initial Maintenance KPI foundation created.

Version 1.1 Expanded KPI categories, dashboards, governance, and implementation guidance.

Version 1.2 Completed industry guidance, maturity model, implementation roadmap, product opportunities, references, and revision history.

Version 1.3 Added canonical Formula Standard-compliant definitions for Mean Time Between Failures (MTBF), Mean Time To Repair (MTTR), Overall Equipment Effectiveness (OEE), and Wrench Time under Controlled Maintenance KPI Definitions, closing the corpus-wide gap identified in the Review-49 program. This page is now the canonical formula dictionary for these four metrics; Maintenance Performance Management and Reliability KPIs & Performance Measurement reference this page rather than redefining them.

Version 1.4 Qualified unsupported performance language and clarified MTBF interpretation, OEE scope, and wrench-time denominator boundaries for publication readiness.