It's as true for maintenance and reliability as it is for every other business function: you can’t improve what you don’t measure.
That’s why tracking the right maintenance metrics is essential. It’s a practical way to see what’s working, where risks are building, and how your maintenance culture is evolving.
Some key performance indicators (KPIs) tell the story of what already happened, which is helpful for benchmarking and long-term planning. Others give you early warning of process gaps, slow responses, or developing equipment issues. Together, they create a clearer picture of equipment uptime, team efficiency, and overall maintenance performance.
The most effective maintenance programs rely on a mix of historical and actionable metrics. This makes it easy to see and address failure patterns, engagement and responsiveness, and opportunities for continuous improvement. With the right combination, your team can make faster, smarter decisions and move closer to a true uptime-driven lean manufacturing operation.
1. Overall Equipment Effectiveness: Essential for Optimizing Processes and Performance
Overall equipment effectiveness (OEE) blends availability, performance, and quality to show how effectively your equipment is producing goods during planned production time. It reveals losses caused by slow cycles, frequent stops, speed loss, and quality defects.
✅ Why it matters
OEE gives reliability teams a powerful KPI for identifying whether downtime, slow cycle times, or quality issues are dragging down manufacturing effectiveness. When paired with real-time monitoring and predictive maintenance, OEE becomes a roadmap for reducing unplanned downtime, supporting uptime/lean manufacturing principles, and maximizing machine performance across the entire production line.
2. Availability: A Core Measure for Minimizing Overall Downtime
Availability measures the percentage of scheduled production time when equipment is capable of running, whether or not it is actually in operation. It accounts for both planned downtime (such as preventive maintenance or changeovers) and unplanned downtime (such as equipment failures or micro stops). Availability reflects how much of the planned production time is truly accessible for value-adding work.
✅ Why it matters
Because availability includes all downtime, both planned and unplanned, it provides a broad view of how effectively a plant manages its scheduled production periods. Low availability signals issues with maintenance scheduling, setup efficiency, staffing, or lingering equipment problems.
By improving availability, teams minimize downtime, support uptime lean manufacturing goals, and ensure equipment is ready when production needs it. This is especially important for plants focused on total productive maintenance and continuous improvement.
3. Equipment Uptime: The Most Direct Indicator of Machine Uptime Health
Equipment uptime measures the actual amount of time equipment is running and producing goods. Unlike availability, uptime does not consider whether the machine should be running according to the production schedule; it simply tracks real runtime.
✅ Why it matters
Equipment uptime is the most direct indicator of machine uptime performance. Tracking this metric helps teams understand how reliably equipment operates during both planned and unplanned windows.
Improving uptime reduces production delays, increases throughput, and strengthens overall equipment effectiveness. When supported by real-time monitoring, AI-powered predictive maintenance, and ongoing expert support, teams can detect failure patterns early and take action that leads to more uptime, fewer disruptions, and greater production line efficiency.
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4. Mean Time Between Failures (MTBF): Strengthening Downtime Prevention and Asset Reliability
MTBF measures the average operating time between one equipment failure and the next, making it a critical indicator of long-term asset health. A high MTBF signals that machinery is stable, components are reliable, and maintenance practices are effective. A low MTBF often reveals deeper mechanical issues such as misalignment, lubrication failures, contamination, bearing wear, or other early-stage failure modes.
✅ Why it matters
Improving MTBF directly supports machine uptime and manufacturing effectiveness. When MTBF begins to trend downward, maintenance teams can use condition monitoring data to pinpoint where failures originate and intervene earlier in the failure curve. This not only helps minimize downtime but also strengthens maintenance strategies and supports continuous improvement across the production line.
In lean manufacturing environments, MTBF is one of the clearest signals that asset reliability is improving or declining. It also shows where to focus next to maximize uptime.
5. Mean Time to Repair (MTTR): A Key Metric for Faster Recovery and More Uptime
MTTR measures the average time it takes to diagnose, repair, test, and restore equipment after a failure. It reflects the efficiency of your maintenance response: technician skill, spare parts logistics, standard operating procedures, troubleshooting precision, and communication between maintenance and operations.
✅ Why it matters
A high MTTR drains operating time, reduces total uptime, and drives up maintenance costs. Reducing MTTR allows teams to return equipment to service faster, minimizing downtime and maximizing production capacity during scheduled time.
When supported by predictive insights such as fault severity, recommended actions, and clear diagnostics, teams reduce guesswork and accelerate the repair process. MTTR is a powerful way to measure the effectiveness of continuous training, planning, and workflows.
6. Planned Maintenance Percentage (PMP): Essential for Maximizing Uptime and Total Productive Maintenance
PMP measures the percentage of maintenance work that is planned in advance versus reactive or emergency repairs. It reflects maintenance culture maturity and how successfully teams have shifted from firefighting to proactive reliability management.
✅ Why it matters
A consistently high PMP aligns with total productive maintenance goals and supports lean manufacturing by reducing disruptions, stabilizing schedules, and helping technicians work more efficiently.
When PMP is supported by predictive maintenance insights, teams can schedule interventions based on real equipment condition rather than generic calendar intervals. This not only helps optimize processes but also reduces unnecessary preventive maintenance tasks and increases overall uptime. PMP is a strong indicator of how well your organization manages maintenance workload, protects production time, and supports long-term equipment effectiveness.
Preventing equipment failures and unplanned downtime is mission critical for manufacturing operations. But not all predictive maintenance solutions are alike. Knowing what questions to ask as you evaluate providers can help you ensure smooth adoption, maximum ROI, and scalable success. 👉 Get the PdM provider evaluation checklist here.
7. Maintenance Backlog: A Continuous Improvement Indicator for Workflow Efficiency
Maintenance backlog measures all open maintenance work including preventive, predictive, corrective, and improvement tasks that have not yet been completed. A balanced backlog shows healthy workflow management; an oversized backlog signals resource limitations, scheduling inefficiencies, or emerging equipment risks.
✅ Why it matters
A growing backlog increases the risk of unplanned downtime, parts shortages, and delayed repairs. It also adds pressure on lean teams, making it harder to prioritize the work that protects uptime.
When backlog visibility is paired with a computerized maintenance management system, teams gain better oversight of asset histories, open work orders, scheduled tasks, and aging repairs. This improves planning, helps ensure smooth operations, and supports continuous improvement by revealing bottlenecks in staffing, planning, or process execution. Reducing backlog is one of the fastest ways to improve uptime and workflow efficiency across the plant.
8. Mean Time to Comment (MTTC): A Real-Time Monitoring Metric for Faster Team Response
MTTC measures the time between a new alert or fault notification and the moment maintenance personnel acknowledge and engage with it. It is one of the strongest behavioral indicators of maintenance responsiveness.
✅ Why it matters
Slow response times often reveal competing priorities, unclear workflows, or insufficient real-time monitoring practices. MTTC helps reliability leaders understand whether alerts are being seen quickly and whether the team is positioned to act before faults escalate into unplanned downtime.
Faster acknowledgment typically correlates with more uptime, fewer sudden failures, and better alignment between maintenance and operations. MTTC is an essential leading indicator for building a data-driven maintenance culture and improving overall equipment effectiveness.
9. Mean Time to Resolution (MTTR): A Critical KPI for Optimizing Processes and Minimizing Downtime
MTTR measures the full time from alert to verified problem resolution, including root-cause identification, planning, repair execution, parts coordination, and confirmation that the asset is healthy again (often validated through sensor data or oil analysis).
✅ Why it matters
This metric gives a far more accurate view of the maintenance process than repair-time-only MTTR. MTTR shows whether teams are resolving issues efficiently, prioritizing appropriately, and applying strong standard operating procedures.
A shorter MTTR means more uptime, less reactive work, and better alignment with production goals. It’s also a powerful KPI for identifying systemic inefficiencies such as parts delays, unclear work instructions, or insufficient staffing so leaders can optimize processes and reduce downtime over time.
10. Mean Time Between Faults (MTBF): A Leading Indicator for Continuous Improvement and Equipment Uptime
MTBF tracks how long equipment runs between recurring faults of the same type. It shows whether issues are truly resolved or whether underlying conditions persist.
✅ Why it matters
Recurring faults disrupt production, undermine preventive maintenance strategies, and erode equipment reliability. A short MTBF signals that teams may be addressing symptoms instead of root causes.
Improving MTBF helps increase equipment uptime, reduce maintenance costs, and enhance the stability of manufacturing processes. It is one of the clearest indicators for continuous improvement, as it highlights whether maintenance interventions provide lasting impact. As predictive maintenance insights improve, MTBF naturally increases, yielding more uptime and more reliable production lines.
With the Right Mix of KPIs, You Can Transform Your Operations
If your goal is more uptime, fewer equipment failures, and a more efficient maintenance operation, tracking the right KPIs is essential. But it’s not enough to measure what happened yesterday. You also need metrics that guide your team’s actions today and shape the improvements you strive for tomorrow.
By blending traditional maintenance KPIs with actionable, process-focused indicators, you'll gain a complete view of asset health, team performance, and system reliability. When paired with predictive maintenance tools and real-time monitoring, these metrics help eliminate unplanned downtime, maximize uptime, and build a stronger maintenance culture.
Want to see how leading manufacturing companies are using these KPIs to maximize uptime, improve equipment performance, and strengthen reliability programs? Our recent webinar Maintenance KPIs That Matter reveals how you can use the data at your fingertips to achieve maintenance and reliability excellence. ▶️ Watch the on-demand replay here.
