How to Track and Analyze Equipment & Machine Downtime

Asset Management · By the FastMaint Team · ~9 min read

A handful of problem machines usually drive most of your unplanned downtime — but when you run dozens or hundreds of assets, they’re hard to spot. This is a practical, two-stage method for finding those problem machines in your data and fixing the real root cause, not just the symptom.

Why Downtime Reports Matter

A downtime report tracks when equipment isn’t operating as intended — whether it’s stopped for repair, waiting on parts, or fully broken down. Read correctly, these reports are how you improve reliability and cut costly disruptions.

The catch is scale. When you run many machines, the few that quietly eat your budget and your uptime are buried in the noise. Analyzing the data the right way is how you pull them out: spot recurring issues, trace root causes, and make maintenance decisions that actually move uptime instead of guessing.

Downtime Metrics: Which Ones Actually Help

A few standard numbers come up in any downtime discussion — but they’re not equally useful, and which one matters depends on your situation. If you run many different types of equipment at one facility (most industrial and facilities teams do), keep this distinction in mind before leaning on any single statistic.

The metric to lead with: total equipment downtime (in hours)

To find problem equipment, measure total downtime in absolute hours per asset, not as a percentage. Raw hours don’t hide anything — if a machine’s downtime doubles, the number doubles, and the problem is impossible to miss.

Useful only for comparing similar assets: MTBF & MTTR

These two are valuable in a narrower situation — comparing equipment of the same type used in similar ways. They’re not facility-wide scorecards.

MTBF tells you how long an asset typically runs between breakdowns. Higher is better. It’s meaningful when you line up like-for-like machines — comparing the MTBF of a pump against a conveyor tells you nothing useful.

MTTR captures how long it takes to get a failed asset running again. Lower is better. A high MTTR often points to parts availability or skill/planning gaps rather than the equipment itself.

Stage 1: How to Find Your Problem Equipment

Stage 2: How to Find the Breakdown Reason & Fix It

Once you have a shortlist of problem equipment, dig into why each one fails. Frequent breakdowns almost always trace to one of five causes — and each has a different fix.

1. Close to end of life

You can keep almost anything running with enough maintenance, but there’s a point where it’s no longer worth it. Metal fatigue, scarce spare parts, lost maintenance skills, or newer equipment that’s simply more efficient are all signals.

Fix: Replace any asset on your list that fits this profile.

2. Poor maintenance practices

Skipped preventive maintenance, low-quality spares, or technicians not performing the job correctly. Watch for the same parts being replaced repeatedly, recurring issues tied to particular supplies, or skipped PM in the work-order history.

Fix: These assets need a better preventive maintenance plan (see our 7 tips to plan equipment preventive maintenance). Technicians may need training, and if poor-quality parts are the culprit, it’s time for a better vendor.

3. Poor operational practices

Operators using equipment incorrectly, or running it beyond what it was designed for. Technician feedback mentioning operator error is a clue; a critical asset that fails often despite proper maintenance may simply be overloaded.

Fix: Improve operator training, add capacity, or rework the operational flow to flatten peak loads.

4. Poorly designed or built

Internal flaws — like inadequate cooling causing overheating. If many identical machines all fail the same way, suspect a design or build issue, and check whether other organizations report the same fault.

Fix: Press the manufacturer to address it, or switch to better equipment from another vendor.

5. Incorrectly installed or set up

Equipment installed wrong, or damaged during install or startup. This looks like a design flaw but stays isolated to a few units rather than every similar machine — and outside research usually won’t surface widespread complaints. Comparing against manufacturer specs gives clues.

Fix: Inspect the affected units and re-install completely where needed.

What “Good” Downtime Looks Like

Industry rules of thumb exist, but here’s the honest caveat: targets vary widely by industry and asset type, and percentage-based benchmarks share the same blind spot we covered above — they can look healthy while absolute downtime hours climb. Treat these as directional context, not the thing you actually manage to.

Why a CMMS Makes This Practical

Every step in this guide depends on one thing: pulling a year of clean cost, downtime, and work-order data on demand, per asset. Spreadsheets and memory can’t do that reliably — if the data was never captured consistently, there’s nothing to analyze. This is where a CMMS earns its keep.

FastMaint is built for small maintenance teams who need this kind of reporting without a six-month rollout or a dedicated IT department. It’s complete enough to run a real downtime analysis — Equipment History, Equipment Downtime, and Work Order History reports out of the box — and simple enough that technicians actually log the work in the first place, which is what makes the data trustworthy. The reporting you need isn’t gated behind a higher tier; nearly everything is included at one price. Whether you run it as a cloud subscription or install and own it outright, the data’s there when you need to analyze it.

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