Maintenance and Reliability

How to Build an MTBF and MTTR Dashboard in Excel

Most maintenance dashboards fail because they start with the chart instead of the event log. Here is the layout that actually works: one row per failure, two formulas, and a trend view that shows a machine getting worse before it stops.

Almost every maintenance dashboard I have seen starts in the wrong place. Someone builds the chart first, then works backward toward the data that would fill it, and ends up with a monthly average that cannot answer the only question worth asking: is this machine getting worse? A dashboard that works starts from an event log, one row per failure, and derives everything else. The two headline numbers, mean time between failures and mean time to repair, are trivial arithmetic once that log exists and nearly impossible to compute honestly when it does not.

The event log is the whole dashboard

Build one sheet with six columns and resist adding more: asset ID, failure start timestamp, repair complete timestamp, failure mode, whether the stop was planned, and a free-text note. Downtime hours is a formula, not an entry, because a human typing a duration will round it and a subtraction will not. Planned versus unplanned needs its own column because including planned maintenance in MTBF is the single most common way these numbers get quietly inflated. Everything on the dashboard should be a pivot over this one table. If a number on your dashboard cannot be traced back to specific rows in it, delete the number.

The two formulas, with a worked example

MTBF is operating time divided by the number of failures. MTTR is total repair time divided by the same count. The trap is the numerator: MTBF uses operating time, not calendar time, so the hours a machine sat idle because there was no work do not belong in it. Take a line scheduled for 720 hours in a month that suffered 3 unplanned failures with an average repair of 2.5 hours. Downtime is 7.5 hours, so operating time is 712.5 hours, MTBF is 237.5 hours and MTTR is 2.5 hours. Availability, the number most plants actually care about, is operating time over scheduled time: 99.0%.

• MTBF in the worked example: 237.5 h
• MTTR in the worked example: 2.5 h
• Availability that follows: 99.0%

The chart that earns its space

Plot rolling MTBF, not monthly MTBF. A monthly bar chart resets every period and hides the thing you are looking for, which is a downward drift over several months. A rolling window of the last ten failures, recomputed on every new event, turns degradation into a visible slope. Put MTTR on a secondary axis, because the two move independently and the combination is diagnostic: falling MTBF with flat MTTR is a machine wearing out, while flat MTBF with rising MTTR is usually a parts availability or skills problem rather than an equipment one.

A monthly average tells you what happened. A rolling window tells you what is happening. Only one of those gives you time to act.

Three mistakes that make the numbers lie

Check these before anyone presents the dashboard

• Counting planned maintenance as a failure, which drags MTBF down and makes a healthy asset look fragile.
• Measuring repair time from technician arrival rather than from the stop, which hides response delay in a number labelled repair.
• Averaging MTBF across dissimilar assets, which produces a plant number that describes no machine you own.

When the spreadsheet stops being enough

A spreadsheet is the right tool up to a few hundred events a year and the wrong one past that, not because Excel cannot hold the rows but because manual entry decays. The tell is the free-text note column going empty: once technicians stop writing what actually broke, the failure-mode analysis dies and you are left with two averages and no cause. At that point the event log needs to come from the maintenance system automatically, and the spreadsheet becomes the analysis layer on top of it rather than the system of record.

Use the MTBF calculator to check your event log math before you build the dashboard around it. Run the numbers first

Published 2026-08-08.