20 Maintenance KPIs Every Plant Manager Must Track in

2026

Introduction

Manufacturing competitiveness in 2026 is no longer determined solely by production capacity or automation. It is increasingly defined by how effectively organisations measure, manage, and improve asset performance. As manufacturers embrace Industry 4.0, Artificial Intelligence (AI), Industrial Internet of Things (IIoT), and digital maintenance platforms, maintenance is evolving from a reactive support function into a strategic business capability that directly influences profitability, operational resilience, sustainability, and customer satisfaction.

Despite this transformation, many maintenance teams continue to rely on lagging indicators such as total maintenance cost or the number of equipment breakdowns. While these metrics provide historical insight, they rarely offer the predictive intelligence needed to prevent failures before they disrupt production.

Leading manufacturers have shifted towards a data-driven reliability culture, where maintenance decisions are guided by real-time Key Performance Indicators (KPIs). These metrics provide early warning signals of declining equipment health, workforce inefficiencies, planning gaps, and asset risks, enabling maintenance leaders to intervene proactively rather than reactively.

Maintenance KPIs are more than operational statistics. They are strategic management tools that align maintenance performance with broader business objectives, including production uptime, product quality, safety, energy efficiency, cost optimisation, and asset lifecycle management.

When monitored consistently through a modern Computerized Maintenance Management System (CMMS), maintenance KPIs empower plant managers to answer critical operational questions such as:

Which assets present the highest reliability risk?
Are preventive maintenance programmes delivering measurable value?
How quickly are maintenance teams restoring failed equipment?
Are maintenance costs increasing without corresponding improvements in asset performance?
Which production lines require reliability improvement initiatives?
Are predictive maintenance investments generating measurable returns?

The answers to these questions determine whether maintenance functions remain reactive cost centres or become strategic contributors to manufacturing excellence.

This article explores the 20 most important maintenance KPIs every plant manager should track in 2026, explaining what each metric measures, why it matters, how to calculate it, and how modern CMMS platforms help transform KPI data into actionable operational intelligence.

Why Maintenance KPIs Matter More Than Ever

Today’s manufacturing facilities generate enormous volumes of operational data from sensors, PLCs, SCADA systems, ERP platforms, MES applications, and connected maintenance software. However, collecting data alone does not improve reliability.

Competitive advantage comes from identifying the metrics that genuinely influence operational performance.

Maintenance KPIs enable organisations to:

Improve equipment availability
Reduce unplanned downtime
Increase Overall Equipment Effectiveness (OEE)
Optimise preventive maintenance programmes
Lower maintenance costs
Improve technician productivity
Extend equipment lifespan
Strengthen regulatory compliance
Improve spare parts planning
Support predictive maintenance initiatives

Rather than measuring maintenance activity, effective KPIs measure maintenance outcomes.

For example, tracking the number of completed work orders provides limited strategic value. Measuring preventive maintenance compliance, Mean Time Between Failures (MTBF), and Mean Time To Repair (MTTR) offers far deeper insight into equipment reliability and maintenance effectiveness.

As maintenance becomes increasingly digital, KPIs also enable executive leadership to monitor operational performance in real time, supporting faster and more informed decision-making across the enterprise.

Characteristics of High-Value Maintenance KPIs

Not every maintenance metric deserves executive attention.

High-performing maintenance organisations focus on KPIs that are:

Actionable

The metric should drive operational improvement rather than simply report historical performance.

Measurable

Reliable data should be consistently available through automated systems rather than manual spreadsheets.

Timely

KPIs should be updated frequently enough to support rapid operational decisions.

Aligned with Business Objectives

Maintenance performance should contribute directly to production, quality, safety, and financial goals.

Easy to Understand

Plant managers, technicians, planners, and executives should interpret KPI trends consistently.

Modern CMMS platforms automate KPI calculation, ensuring that decision-makers receive accurate and timely insights without extensive manual reporting.

KPI 1 – Overall Equipment Effectiveness (OEE)

Why It Matters

Overall Equipment Effectiveness (OEE) is widely recognised as the most comprehensive manufacturing KPI because it combines three essential dimensions of production performance:

Availability
Performance
Quality

Rather than measuring maintenance in isolation, OEE demonstrates how equipment reliability directly influences manufacturing productivity.

A decline in OEE often indicates recurring equipment failures, excessive changeover times, operator inefficiencies, or quality losses—all of which may require maintenance intervention.

Formula

OEE = Availability × Performance × Quality

World-Class Benchmark

85% or higher

Improvement Strategies

Reduce equipment failures
Improve preventive maintenance compliance
Optimise changeovers
Eliminate recurring defects
Increase equipment reliability

KPI 2 – Mean Time Between Failures (MTBF)

Why It Matters

Mean Time Between Failures measures the average operating time between equipment failures.

It is one of the most important indicators of equipment reliability and asset health.

Increasing MTBF demonstrates that maintenance programmes are successfully preventing failures rather than merely responding to them.

Formula

MTBF = Total Operating Time ÷ Number of Failures

World-Class Goal

Continuously increasing MTBF.

Higher values indicate better equipment reliability.

Improvement Strategies

Root Cause Analysis (RCA)
Predictive maintenance
Condition monitoring
Improved lubrication
Better operator inspections

KPI 3 – Mean Time To Repair (MTTR)

Why It Matters

Equipment failures cannot always be avoided.

The speed at which maintenance teams restore production significantly influences operational performance.

Mean Time To Repair measures maintenance responsiveness and repair efficiency.

Lower MTTR generally reflects:

Better technician skills
Improved planning
Faster spare parts availability
Standardised repair procedures
Mobile maintenance execution

Formula

MTTR = Total Repair Time ÷ Number of Repairs

Target

Continuously decreasing MTTR.

Improvement Strategies

Digital work orders
Mobile CMMS
QR code asset identification
Standard repair procedures
Spare parts optimisation

KPI 4 – Asset Availability

Why It Matters

Availability measures the percentage of scheduled production time during which equipment is operational and capable of producing output.

Unlike MTBF or MTTR, availability reflects the actual business impact of maintenance performance on production.

Even small improvements in asset availability can significantly increase annual production capacity without investing in additional machinery.

Formula

Availability (%) = (Operating Time ÷ Planned Production Time) × 100

Target

Above 95% for critical production assets.

Improvement Strategies

Improve preventive maintenance planning
Reduce emergency repairs
Increase predictive maintenance coverage
Eliminate recurring equipment failures

KPI 5 – Preventive Maintenance Compliance

Why It Matters

Preventive maintenance programmes only deliver value when maintenance activities are completed on schedule.

Delayed inspections, postponed servicing, and missed lubrication tasks frequently become the root causes of future equipment failures.

Preventive Maintenance Compliance measures how consistently maintenance teams execute planned maintenance.

Formula

PM Compliance = (Completed PM Tasks ÷ Scheduled PM Tasks) × 100

World-Class Benchmark

95–100%

Improvement Strategies

Automated scheduling
Mobile maintenance
Technician accountability
Workload balancing
CMMS reminders

High compliance rates reduce equipment failures while improving long-term asset reliability.

KPI 6 – Planned Maintenance Percentage (PMP)

Why It Matters

World-class maintenance organisations spend most of their time performing planned work rather than responding to unexpected equipment failures.

Planned Maintenance Percentage measures how much maintenance effort is proactive.

Formula

PMP = (Hours Spent on Planned Maintenance ÷ Total Maintenance Hours) × 100

Industry Benchmark

World-Class: 80–90%
Developing Plants: 60–75%
Reactive Plants: Below 50%

A high Planned Maintenance Percentage indicates mature maintenance planning processes, improved reliability, and lower emergency maintenance costs.

Improvement Strategies

Develop structured maintenance schedules
Increase preventive maintenance coverage
Implement predictive maintenance technologies
Reduce reactive work orders
Use CMMS planning and scheduling tools to optimise labour allocation

KPI 7 – Reactive Maintenance Percentage

Why It Matters

Reactive maintenance remains one of the largest hidden cost drivers in manufacturing. Emergency repairs typically cost three to five times more than planned maintenance because they involve unplanned labour, production losses, overtime, expedited spare parts, and quality risks.

Reactive Maintenance Percentage measures how much maintenance effort is devoted to emergency work rather than planned activities.

World-class manufacturers increasingly target low reactive maintenance levels because high-performing plants understand that reliability is created through planning, inspection, condition monitoring, and predictive intervention.

Formula

Reactive Maintenance Percentage = (Reactive Maintenance Hours ÷ Total Maintenance Hours) × 100

Benchmark

World-Class: Less than 20%
Average Plants: 20–40%
Reactive Plants: Above 40%

Improvement Strategies

Strengthen preventive maintenance programmes
Implement condition monitoring
Increase predictive maintenance coverage
Improve spare parts availability
Conduct Root Cause Analysis (RCA)
Use CMMS planning tools

A decreasing reactive maintenance percentage generally indicates improving asset reliability.

KPI 8 – Maintenance Backlog

Why It Matters

Maintenance backlog measures the volume of pending maintenance work that has not yet been completed.

A moderate backlog is healthy because it provides planners with work visibility and scheduling flexibility. However, excessive backlog increases failure risks, delays preventive maintenance, and contributes to unplanned downtime.

Maintenance backlog is a leading indicator of future reliability problems.

Formula

Maintenance Backlog (Weeks) = Total Outstanding Maintenance Hours ÷ Available Labour Hours per Week

Recommended Benchmark

Optimal: 2–4 weeks
Risk Zone: More than 6 weeks

Improvement Strategies

Improve planning and scheduling
Prioritise work orders
Eliminate low-value tasks
Increase PM effectiveness
Optimise workforce allocation

Modern CMMS systems help maintenance teams visualise backlog by priority, asset criticality, and resource availability.

KPI 9 – Maintenance Cost per Asset

Why It Matters

Understanding maintenance expenditure at the asset level enables better lifecycle decisions.

Some assets become increasingly expensive to maintain due to ageing, obsolescence, poor design, or chronic reliability problems.

Maintenance Cost per Asset supports decisions related to:

Asset replacement
Reliability improvements
Capital investment
Maintenance optimisation

Formula

Maintenance Cost per Asset = Total Maintenance Cost ÷ Number of Assets

What to Monitor

Track:

Cost trends over time
Cost by asset category
Cost by production line
Cost by equipment criticality

Improvement Strategies

Asset criticality analysis
Reliability-centred maintenance
Root Cause Analysis
Predictive maintenance
Asset replacement planning

KPI 10 – Maintenance Cost as a Percentage of Replacement Asset Value (RAV)

Why It Matters

This KPI evaluates maintenance efficiency relative to total asset value.

It helps determine whether maintenance expenditure is appropriate compared with the replacement cost of equipment.

Formula

Maintenance Cost % RAV = (Annual Maintenance Cost ÷ Replacement Asset Value) × 100

Industry Benchmark

World-Class: 2–3%
Average: 3–5%
High Cost: Above 5%

Example

If:

Annual maintenance cost = £800,000
Asset replacement value = £25 million

Then:

Maintenance Cost % RAV:

(£800,000 ÷ £25,000,000) × 100 = 3.2%

This indicates reasonable maintenance efficiency.

Improvement Strategies

Improve planning
Increase PM effectiveness
Reduce repeat failures
Extend equipment life
Optimise spare parts

KPI 11 – Schedule Compliance

Why It Matters

Maintenance schedules create operational discipline.

Schedule Compliance measures whether planned maintenance work is completed according to schedule.

Poor compliance leads to:

Delayed inspections
Increased failures
Higher reactive maintenance
Greater operational risk

Formula

Schedule Compliance = (Completed Scheduled Work ÷ Planned Work) × 100

Benchmark

World-Class: Above 90%

Improvement Strategies

Better planning
Labour balancing
Mobile work orders
Realistic schedules
Daily maintenance reviews

High schedule compliance often correlates strongly with high asset reliability.

KPI 12 – Work Order Completion Rate

Why It Matters

Work orders represent the operational heartbeat of maintenance.

Low completion rates may indicate:

Resource shortages
Planning inefficiencies
Excessive emergencies
Poor technician utilisation

Formula

Work Order Completion Rate = (Completed Work Orders ÷ Total Work Orders) × 100

Benchmark

Target: Above 90%

Improvement Strategies

Digital work orders
Mobile CMMS
QR asset tracking
Improved scheduling
Standard job plans

CMMS platforms automate work order workflows, significantly improving execution efficiency.

KPI 13 – Technician Productivity

Why It Matters

Maintenance effectiveness depends not only on workforce size but also on productive labour utilisation.

Technician Productivity measures how much technician time is spent on value-adding activities.

Many organisations discover that technicians spend considerable time searching for:

Information
Spare parts
Tools
Documentation
Approvals

Formula

Technician Productivity = (Productive Maintenance Hours ÷ Total Available Hours) × 100

Benchmark

World-Class: 65–75%

Improvement Strategies

Mobile CMMS
Digital work instructions
QR asset identification
Better planning
Spare parts availability

Even a 10% improvement in technician productivity can significantly increase maintenance capacity.

KPI 14 – Spare Parts Inventory Turnover

Why It Matters

Excess inventory ties up working capital, while insufficient inventory creates production risks.

Spare Parts Inventory Turnover measures inventory efficiency.

Formula

Inventory Turnover = Annual Spare Parts Usage ÷ Average Inventory Value

High Turnover Indicates

Effective inventory management
Reduced obsolete stock
Better forecasting
Lower carrying costs

Improvement Strategies

ABC inventory analysis
Critical spares classification
Demand forecasting
CMMS inventory management
Supplier collaboration

Modern maintenance organisations integrate CMMS, procurement, and inventory systems to optimise spare parts availability without increasing stock levels.

KPI Relationships: The Maintenance Performance Chain

Individual KPIs provide valuable insights, but the greatest value comes from understanding how KPIs influence one another.

For example:

Higher PM Compliance
↓
Fewer Failures
↓
Higher MTBF
↓
Lower MTTR
↓
Reduced Downtime
↓
Higher Availability
↓
Improved OEE
↓
Greater Production Output

This cause-and-effect relationship transforms maintenance KPIs from isolated metrics into an integrated reliability management system.

Executive KPI Dashboard for 2026

Plant managers should monitor a balanced KPI portfolio:

Reliability KPIs

MTBF
MTTR
Asset Availability
OEE

Maintenance Execution KPIs

PM Compliance
Schedule Compliance
Work Order Completion

Financial KPIs

Maintenance Cost per Asset
Maintenance Cost % RAV
Inventory Turnover

Workforce KPIs

Technician Productivity
Planned Maintenance Percentage

Strategic KPIs

Reactive Maintenance %
Backlog
Predictive Maintenance Coverage

Leading manufacturers increasingly use AI-powered CMMS dashboards to visualise KPI trends in real time rather than relying on monthly spreadsheet reports.

KPI 15 – Predictive Maintenance Coverage

Why It Matters

As manufacturing plants adopt Industry 4.0 technologies, maintenance strategies are shifting from time-based servicing to condition-based and predictive maintenance. Predictive Maintenance Coverage measures the proportion of critical assets monitored using AI, IIoT sensors, vibration analysis, thermal imaging, oil analysis, or other predictive techniques.

A higher coverage percentage indicates greater organisational maturity in anticipating failures before they disrupt production.

Formula

Predictive Maintenance Coverage (%) = (Assets Under Predictive Monitoring ÷ Total Critical Assets) × 100

Benchmark

World-Class: Above 80%
Developing Organisations: 40–70%
Reactive Organisations: Below 30%

Improvement Strategies

Deploy IIoT sensors on critical equipment
Integrate predictive analytics with CMMS
Prioritise high-risk assets
Implement AI-based failure prediction models
Review predictive alerts during weekly maintenance planning

KPI 16 – Emergency Work Order Percentage

Why It Matters

Emergency work orders are expensive because they interrupt planned schedules, require immediate labour allocation, increase overtime, and often result in production losses.

Monitoring the percentage of emergency work orders provides a clear indication of maintenance planning effectiveness.

Formula

Emergency Work Order Percentage = (Emergency Work Orders ÷ Total Work Orders) × 100

Benchmark

World-Class: Less than 10%
Average Plants: 10–20%
High Risk: Above 20%

Improvement Strategies

Improve preventive maintenance compliance
Increase predictive maintenance adoption
Conduct failure mode analysis
Standardise inspection routes
Optimise maintenance scheduling

Reducing emergency work orders improves labour utilisation, equipment availability, and maintenance costs.

KPI 17 – First-Time Fix Rate (FTFR)

Why It Matters

First-Time Fix Rate measures how often technicians resolve equipment issues during their initial visit without requiring follow-up work.

A high FTFR reflects effective planning, technician competence, spare parts availability, and access to accurate maintenance information.

Formula

First-Time Fix Rate = (Successful First Repairs ÷ Total Repairs) × 100

World-Class Benchmark

Above 90%

Improvement Strategies

Digital work instructions
Mobile CMMS access
QR code asset identification
Technician training
Accurate spare parts planning
Standardised repair procedures

Higher FTFR reduces repeat failures, improves technician productivity, and minimises production disruption.

KPI 18 – Asset Health Index (AHI)

Why It Matters

The Asset Health Index is an aggregated score that reflects the current condition and operational risk of an asset based on multiple variables, including:

Equipment age
Failure frequency
Maintenance history
Sensor data
Operating conditions
Inspection findings
Remaining Useful Life (RUL)

Rather than reacting to individual alarms, maintenance teams can prioritise interventions based on overall asset health.

Typical Rating Scale

90–100: Excellent
75–89: Good
60–74: Moderate Risk
Below 60: High Risk

Improvement Strategies

Continuous condition monitoring
Predictive maintenance
Reliability-centred maintenance
Root Cause Analysis
Asset refurbishment or replacement

AI-powered CMMS platforms automatically calculate Asset Health Index values by combining maintenance and operational data.

KPI 19 – Maintenance Schedule Adherence

Why It Matters

Maintenance schedules are effective only when executed as planned.

Schedule adherence measures whether maintenance teams perform work at the planned time without unnecessary delays or rescheduling.

Consistent schedule adherence improves maintenance efficiency and production coordination.

Formula

Schedule Adherence (%) = (Maintenance Tasks Completed on Schedule ÷ Planned Maintenance Tasks) × 100

Benchmark

Above 90%

Improvement Strategies

Weekly planning meetings
Resource optimisation
Digital scheduling
Mobile technician notifications
Better coordination with production teams

KPI 20 – Maintenance Return on Investment (Maintenance ROI)

Why It Matters

Executive leadership increasingly expects maintenance departments to demonstrate measurable business value.

Maintenance ROI evaluates whether maintenance investments generate financial returns through:

Reduced downtime
Increased production output
Lower maintenance costs
Improved equipment reliability
Extended asset life
Higher Overall Equipment Effectiveness (OEE)

Formula

Maintenance ROI = (Financial Benefits – Maintenance Investment) ÷ Maintenance Investment × 100

Example

A manufacturer invests £500,000 in a predictive maintenance programme and achieves:

£850,000 reduction in downtime losses
£150,000 maintenance cost savings

Total benefit:

£1,000,000

Maintenance ROI:

((£1,000,000 – £500,000) ÷ £500,000) × 100 = 100%

Maintenance leaders increasingly use ROI metrics to justify investments in AI, IIoT, digital maintenance, and CMMS platforms.

Building an Executive Maintenance KPI Dashboard

Tracking twenty KPIs individually can overwhelm maintenance teams. High-performing organisations simplify decision-making by consolidating operational metrics into a real-time executive dashboard.

An effective dashboard should include:

Reliability

Overall Equipment Effectiveness (OEE)
Asset Availability
MTBF
MTTR
Asset Health Index

Maintenance Execution

Preventive Maintenance Compliance
Planned Maintenance Percentage
Schedule Compliance
Emergency Work Order Percentage
Work Order Completion Rate

Workforce Performance

Technician Productivity
First-Time Fix Rate
Maintenance Backlog

Financial Performance

Maintenance Cost per Asset
Maintenance Cost as % of RAV
Spare Parts Inventory Turnover
Maintenance ROI

Predictive Maintenance

Predictive Maintenance Coverage
Critical Asset Health
Remaining Useful Life (RUL)
AI-generated maintenance recommendations

With a live CMMS dashboard, plant managers can identify emerging reliability issues, prioritise resources, and make evidence-based decisions before failures impact production.

How MaintWiz CMMS Supports KPI-Driven Maintenance Excellence

Maintenance KPIs are only valuable when supported by reliable, real-time data. Many organisations still rely on spreadsheets and manual reporting, which often results in delayed insights and inconsistent calculations.

MaintWiz CMMS provides a unified platform that automates KPI collection, analysis, and reporting across the maintenance lifecycle.

Centralised Asset Intelligence

MaintWiz maintains a comprehensive digital asset register containing equipment specifications, maintenance history, inspection records, warranties, manuals, and asset criticality. This creates a single source of truth for reliability analysis.

Automated Preventive Maintenance

The platform automatically schedules preventive maintenance based on calendar dates, runtime hours, production cycles, meter readings, or condition-based triggers, improving preventive maintenance compliance and reducing reactive work.

AI-Powered Predictive Maintenance

MaintWiz integrates with IIoT devices and condition-monitoring systems to analyse vibration, temperature, lubrication quality, electrical parameters, and other sensor data. AI models detect developing equipment issues, enabling maintenance teams to intervene before failures occur.

Mobile Work Order Management

Technicians receive digital work orders on mobile devices with QR code asset identification, inspection checklists, safety procedures, technical documents, and spare parts information. Real-time updates improve schedule compliance and technician productivity.

Advanced Maintenance Analytics

Interactive dashboards provide real-time visibility into:

OEE
MTBF
MTTR
Asset Availability
Preventive Maintenance Compliance
Maintenance Backlog
Technician Productivity
Maintenance Costs
Spare Parts Consumption
Asset Health Scores

These dashboards enable maintenance leaders to monitor trends, benchmark performance, and identify opportunities for continuous improvement.

A Practical 90-Day Maintenance KPI Improvement Roadmap

Days 1–30: Assess and Establish Baselines

Focus Areas:

Audit existing maintenance processes
Create an asset criticality matrix
Define KPI ownership
Configure CMMS dashboards
Capture baseline performance data

Deliverables:

Asset Register
Maintenance KPI Baseline
Reliability Assessment
Executive Dashboard Framework

Days 31–60: Standardise and Digitise

Focus Areas:

Digitise preventive maintenance schedules
Deploy mobile work orders
Implement QR code asset tracking
Standardise job plans
Train maintenance teams on KPI reporting

Deliverables:

Digital Maintenance Workflows
Automated KPI Reporting
Mobile Maintenance Deployment
Improved Schedule Compliance

Days 61–90: Optimise and Continuously Improve

Focus Areas:

Introduce predictive maintenance
Integrate IIoT sensor data
Analyse KPI trends
Conduct Root Cause Analysis for recurring failures
Review executive performance monthly

Deliverables:

AI-driven predictive maintenance
Continuous KPI monitoring
Reliability improvement initiatives
Executive maintenance scorecards

By following this structured roadmap, organisations can transition from reactive maintenance management to a KPI-driven culture focused on asset reliability, operational excellence, and measurable business outcomes.

Conclusion

In 2026, maintenance success will be defined not by the number of work orders completed, but by the ability to measure, interpret, and continuously improve the indicators that drive operational performance.

The twenty maintenance KPIs outlined in this guide provide a comprehensive framework for evaluating reliability, maintenance execution, workforce productivity, financial efficiency, and predictive maintenance maturity. Together, they offer plant managers a balanced view of maintenance performance, enabling informed decisions that improve equipment availability, reduce downtime, optimise costs, and extend asset life.

When these KPIs are monitored through an AI-powered CMMS platform, maintenance evolves from a reactive support function into a strategic driver of manufacturing excellence. Organisations that embed KPI-driven decision-making into their maintenance strategy will be better positioned to achieve higher Overall Equipment Effectiveness, stronger operational resilience, and sustainable competitive advantage in the era of Industry 4.0.

Frequently Asked Questions

1. What are maintenance KPIs?

Maintenance KPIs (Key Performance Indicators) are measurable metrics used to evaluate maintenance performance, equipment reliability, workforce productivity, maintenance costs, and overall asset effectiveness.

2. Which maintenance KPI is the most important?

Overall Equipment Effectiveness (OEE) is widely regarded as the most comprehensive maintenance KPI because it combines equipment availability, performance, and product quality into a single metric.

3. What is a good MTBF value?

There is no universal MTBF benchmark because it varies by equipment type and industry. However, increasing MTBF over time generally indicates improving equipment reliability.

4. How does a CMMS improve maintenance KPIs?

A CMMS automates preventive maintenance schedules, manages work orders, tracks asset history, monitors inventory, and provides real-time dashboards that improve maintenance planning and KPI reporting.

5. Why should plant managers monitor maintenance KPIs?

Maintenance KPIs help plant managers reduce downtime, improve equipment reliability, optimise maintenance costs, increase technician productivity, and support data-driven operational decisions.

6. Which KPIs are essential for predictive maintenance?

Important predictive maintenance KPIs include Asset Health Index, Predictive Maintenance Coverage, MTBF, MTTR, Remaining Useful Life (RUL), equipment availability, and emergency work order percentage.