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Downtime Tracking Software: How It Works and 5 Tools Compared (2026)
TL;DR
Downtime tracking software records every time a machine or line stops, how long it stood still and why, then ranks the reasons by the time they cost. Good tools take the stop and restart straight from the machine signal, so no stop is missed or rounded, and ask the operator for the reason on the line in a few taps.
The result is downtime by cause, machine and shift, the input every OEE and continuous improvement effort needs. Below: how it works on the shop floor, what to record, the tracking methods compared and 5 tools.
- Why it matters: Knowing that you were down for 10 minutes is easy. Knowing why (and having proof) is hard. Look for software that validates root causes.
- Automated vs. Manual: The best tools pull start/stop signals directly from the PLC, removing operator bias. Manual logsheets systematically underreport downtime, since short and frequent stops often go unlogged.
- Video Evidence: With its AI camera add-on, Fabrico captures Video Clips of the downtime event, ending the "I don't know what happened" excuses.
- Maintenance Link: Tracking downtime is useless if you don't fix the machine. Top tools link the "Stop Event" directly to a "Work Order."
What downtime tracking software does on the shop floor
- Catches stops on connected machines as they happen, with start time and duration from the machine, including the short ones nobody writes down.
- Gets the reason while people still remember it: the operator tags the cause at the line, not at the end of the shift.
- Separates planned from unplanned stops, so breaks, cleaning and changeovers do not hide the breakdowns.
- Ranks the causes by total time, frequency and average duration, per line and shift, so the team knows which loss to attack first.
- Feeds OEE: stop time becomes availability loss, slow running and micro-stops become performance loss.
How downtime is captured in Fabrico
- The signal. Fabrico reads stop and run from the PLC, from a Fabrico IoT device with sensors on older machines, or from a camera where there is no signal. Lines without sensors use manual mode with quick buttons for the most used reasons.
- The reason. When the line stops, the operator sees the downtime counter and picks the machine, then the reason, red for unplanned and amber for planned, with an optional comment. Stops excluded from OEE, such as a regulatory inspection, still show in total downtime.
- The clean-up. Unclassified time is easy to fix later: select a stretch, merge or split it and give it a reason. Stops shorter than the micro-stop threshold you set are not logged one by one but still count as lost speed.
- The evidence. On camera lines, the system suggests the likely reason for an unclassified stop and keeps the clip, so the shift lead confirms it instead of guessing.
- The follow-up. OEE analytics show the top 10 unplanned and planned reasons and a stoppage table with downtime, frequency and average duration by line. A stop reason can also be configured to open a maintenance task, so breakdowns reach the technicians in the same system.
Want to see your own stops ranked? Book a demo or contact us.
What to record for every stop
| Field | Why it matters |
|---|---|
| Start time and duration | Comes from the machine, so the total is exact and nobody rounds it |
| Machine | Shows which machine in the line actually stopped the flow |
| Reason and reason group | Turns minutes into causes you can act on |
| Planned or unplanned | Keeps breaks and cleaning out of the breakdown count |
| Product and shift | Reveals stops that only happen on one product or one crew |
| Comment or clip | Gives engineers the context for a root cause analysis |
Who uses downtime tracking
- Operators tag the reason in seconds and see the line status on the shop-floor TV.
- Shift leads react to a long stop while it is still running.
- Plant managers open the morning meeting with the top downtime reasons of the last 24 hours.
- Continuous improvement and maintenance engineers pick the next project from a Pareto of causes and check whether the fix held.
Downtime tracking methods compared
| Method | What it catches | What it misses |
|---|---|---|
| Paper log at the line | Long, memorable breakdowns | Short stops, exact durations, most reasons |
| Spreadsheet after the shift | Totals someone remembers | Timing, small stops, consistency between shifts |
| Machine signal only | Stops and their exact duration | Why the machine stopped |
| Signal plus operator reason (light MES) | Stops, their duration and their cause | Causes the operator did not see |
| Signal, reason and camera evidence | Stops, their cause and, on camera lines, the clip to confirm it | Needs a camera on the line |
How we compared manufacturing downtime tracking software
In 2026, many factories still track downtime on whiteboards or Excel sheets. The operator writes: "10:00 - 10:15: Machine Stopped."
This data is usually a guess, and it provides zero insight into how to prevent it from happening again.
Manufacturing downtime tracking software connects directly to your machinery (via PLC/IoT) to capture the exact second the line stops. But capturing the time is just the first step.
You need to capture the reason.
We reviewed the top 5 tools that help you not just "keep score," but actually win back your capacity.
Each tool below is compared on how it captures the stop and the reason behind it. Fabrico's downtime tracking software, part of its MES and OEE platform, records stops and their duration straight from the machine, and operators tag the cause.
1. Fabrico (Best for Stop Causes and Follow-up)
The Verdict: The complete package. It combines Automated Tracking (PLC), Visual Evidence (Camera), and Resolution (Maintenance) in one platform.
Fabrico stands out because it doesn't treat downtime as just a number; it treats it as a problem to be solved. While other tools give you a dashboard, Fabrico gives you a "Zoom-In" into reality.
By connecting the downtime event to the maintenance workflow, it lets a technician open a work order from any stop that needs a repair, so the stop leads to a fix, not just a report.
Key Downtime Features:
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Inefficiencies Zoom-In (AI camera add-on): When the PLC detects a stop, Fabrico grabs the video clip from the line camera. You can watch the jam happen. No guessing.
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Stop Reasons at the Line: Operators tag the cause of each stop on a tablet, and stops coded as breakdown or waiting for maintenance show which lines need a technician.
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The action link: Unlike pure monitoring tools, Fabrico lets a technician open a Maintenance Work Order straight from the logged stop.
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Micro-Stop Detection: Short stops that operators rarely write down are detected and counted, so they show up in OEE instead of disappearing.
Best For: Factories that want to identify and fix the root causes of lost production.
2. MachineMetrics (Best for CNC & Discrete)
The Verdict: The industry standard for high-frequency data collection from CNC machines.
MachineMetrics is a powerhouse for precision machining. It plugs directly into the control ports of CNCs (Fanuc, Haas, etc.) and visualizes spindle load, feed rate, and status.
Its downtime tracking is incredibly precise, often detecting issues millisecond-by-millisecond.
Pros:
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Plug-and-play adapters for most CNC brands.
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Operator tablets allow for easy "Reason Code" entry.
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Predictive tool wear notifications.
Considerations:
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Not a CMMS: It identifies the stop perfectly, but managing the repair (spare parts, technician scheduling) requires a separate system.
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Niche: Less effective for manual assembly or continuous process lines compared to CNCs.
Best For: Precision machine shops and discrete manufacturing.
3. Vorne XL (Best for Visual Management)
The Verdict: The classic "Hardware Scoreboard" solution. Simple, visible, and effective for shop floor motivation.
Vorne is famous for its XL productivity appliance, a physical hardware box and LED display you mount on the line. It shows the target count vs. actual count in huge red/green numbers.
It is the ultimate tool for "Gamification" on the floor.
Pros:
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Hardware based: Very stable, doesn't rely on complex server IT.
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High Visibility: The LED scoreboard drives immediate operator behavior.
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Simple Setup: "Peel and stick" sensor installation.
Considerations:
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Data Silo: The data lives in the Vorne ecosystem. Integrating it with your Maintenance Software or ERP can be tricky.
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Visual Context: It tells you that you stopped; ask Vorne how it shows why (visually).
Best For: Factories that want a simple, visible scoreboard to motivate operators.
4. Evocon (Best for Simplicity)
The Verdict: A lightweight, cloud-based OEE tracker that is easy to deploy on legacy lines.
Evocon focuses on "OEE made simple." It uses simple IoT sensors to count products and detect stops. Its dashboard is clean and intuitive, making it a favorite for factories replacing paper logs for the first time.
It tracks downtime reasons well via an operator tablet interface.
Pros:
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Very intuitive user interface.
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Works on any device (Cloud-based).
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Good "Shift View" visualization.
Considerations:
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Limited Depth: Puts less emphasis on the deep maintenance planning and inventory features of a full MOM platform like Fabrico.
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Manual inputs: Heavy reliance on operators manually selecting downtime reasons.
Best For: SME manufacturers needing a quick, standalone OEE solution.
5. Worximity (Best for Financial Visualization)
The Verdict: Focuses on the "Cost of Downtime," translating stopped minutes into dollars lost.
Worximity uses "Tile" dashboards to visualize production. Its unique angle is connecting OEE to financials.
It will show you not just "10 minutes down," but "$400 lost." This is very effective for getting buy-in from upper management.
Pros:
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"Tile+" dashboards are highly customizable.
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Strong focus on financial impact metrics.
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Quick deployment via wireless sensors.
Considerations:
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Reporting Focus: Great at showing the problem/cost, but fewer tools to manage the physical execution of the fix.
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Mobile Experience: Dashboard focused, less "Technician Workflow" focused.
Best For: Food & Beverage plants focused on yield and cost reduction.
Comparison Matrix: The 2026 Landscape
| Feature | Fabrico | MachineMetrics | Vorne XL | Evocon | Worximity |
| Primary Approach | Action (OEE + Maint) | Data (CNC IoT) | Visual (Hardware) | Simple Cloud | Financial Cost |
| Video Evidence | ✅ Zoom-In | Varies | Varies | Varies | Varies |
| Work Order from the Stop | ✅ Opened from the logged stop | Varies Integration | Varies | Varies | Varies Integration |
| Deployment | Software / IoT | Hardware Adapter | Hardware Box | IoT Sensors | Wireless IoT |
| Best Asset Type | All (Line/Process) | CNC / Discrete | Conveyor / Line | Packaging / Line | Food / Bev |
Conclusion: Don't Just Watch the Scoreboard
If you want to motivate operators, buy Vorne. If you want deep CNC data, buy MachineMetrics.
But if you want to eliminate downtime by connecting the Stop Event to the Maintenance Fix and validating it with Video, Fabrico brings all three together in one platform.
Stop counting losses. Start fixing them.
Book a demo and see Fabrico’s video downtime tracking.
Frequently asked questions
What should downtime tracking software capture?
When the line stopped, for how long, and why, with the reason attached at the time rather than reconstructed later. Duration without a reason tells you that you have a problem but not which one.
Should operators enter downtime reasons manually?
Ideally the stop is detected automatically and the operator only confirms or picks a reason. Manual start and stop entry is where data quality dies, because it competes with the actual job of restarting the line.
How many reason codes should you have?
Few enough to pick from a single screen without scrolling, typically well under twenty at the top level. Long lists get resolved to whatever is nearest the thumb, which quietly corrupts the analysis.
What threshold counts as downtime?
Whatever you choose, applied consistently. The common mistake is setting it high enough to exclude short stops, which hides the losses that often matter most.
See micro stops.
How do you know the data is trustworthy?
Compare total recorded downtime against the gap between planned and actual output for the same period. If they do not roughly reconcile, something is not being captured, and that gap is usually where the real loss is hiding.
Turn downtime into a number your team can actually act on.
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Real Fabrico tiles, sample data.