Know the Moment a Machine Stops. Know Why Before the Shift Ends.
Track downtime automatically as it happens, capture reason codes while the event is still fresh, and give your team the visibility to reduce lost time instead of explaining it later.
10in6 turns machine stop events, operator context, and response activity into downtime data your team can trust, analyze, and act on.
Most plants know they have downtime.
What they often do not have is a reliable record of when it started, why it happened, how long it lasted, and how much production it actually cost.
Too often, downtime is reconstructed at the end of the shift from memory, notes, or broad categories that hide the real issue. The stop happened hours ago. The line is running again. The supervisor asks what went wrong. A reason gets written down anyway.
But it was not really measured.
It was guessed.
And when downtime is guessed, the analysis built on top of it gets weaker too. Pareto charts point at the wrong priorities. Recurring stops get buried. MTBF and MTTR become less meaningful. Teams hear about problems, but they cannot see clearly which ones are actually costing the most.
10in6 changes that by capturing downtime from the event itself.
How 10in6 Downtime Tracking works
The stop is detected automatically
10in6 can detect machine stop events directly from connected machine or PLC signals. In many environments, the system knows the moment production stops instead of waiting for someone to record it later.
At the same time, related workflows such as Andon visibility can be triggered so the stop is not only recorded, but also seen.
The reason is captured while it is happening
Instead of asking operators to remember the event later, 10in6 supports reason code capture while the stop is still active or immediately after it occurs.
That gives the downtime event context while the details are still accurate.
The duration is measured from stop to restart
The event duration is built from the actual stop and restart timing, not filled in from memory at the end of the shift.
That makes the data more trustworthy and gives the team a better foundation for analysis.
The events build into patterns over time
As downtime events accumulate, the system turns them into usable analysis. Teams can trend reason codes, compare shifts and lines, and identify the recurring stops that deserve attention first.
This is where downtime tracking becomes more than a log. It becomes a decision-making tool.
What you can see
With 10in6 Downtime Tracking, your team can see:
- Downtime by machine, line, shift, product, and time period
- Planned vs. unplanned downtime
- Recurring reason codes and chronic stoppages
- Stop frequency and stop duration
- Downtime trends over time
- The events contributing to OEE loss
- The downtime history behind maintenance follow-up
Why Pareto matters here
Pareto analysis is only as useful as the data underneath it.
If stops are entered late, inconsistently, or from memory, the Pareto may still look neat, but it will not tell the team where the biggest production losses really are.
When the stop timing and reason are captured properly, the Pareto becomes a tool for prioritization instead of just another chart.
Why it matters
A downtime event is more than a record of lost minutes. It is one of the clearest signals of where performance is being eroded.
When downtime is visible in real time and categorized clearly, supervisors can respond faster, plant managers can see which losses are recurring, and maintenance teams can work from better information. That improves not only the response to the current issue, but the quality of the improvement work that follows.
It also strengthens the rest of the system. Better downtime data improves OEE accuracy, sharpens production reporting, and makes follow-up workflows more effective.
Connected to the rest of MES
Downtime tracking questions
- How does 10in6 know when a machine is down?
- In many environments, 10in6 can detect machine stop events directly from connected machine or PLC signals. The exact method depends on the equipment and available data points.
- Can downtime reason codes be customized?
- Yes. Reason code structures can be configured to reflect how your operation categorizes downtime and what level of detail your team needs.
- What if an operator forgets to enter a reason code?
- The system can still capture the timing of the event. How missing context is handled depends on the workflow configured for the deployment.
- Can downtime trigger a CMMS work order?
- Yes, when CMMS is part of the deployment, downtime events can support maintenance follow-up workflows and work order creation.
- Can 10in6 support MTBF and MTTR analysis?
- Yes. Because stop and restart timing are captured as events, the system can support more meaningful reliability analysis than end-of-shift reconstruction.
- Can we separate planned and unplanned downtime?
- Yes. The system can be configured so your team can distinguish between expected stops and true production losses.
Need this configured around your actual equipment and workflows?
Every 10in6 deployment includes our team — connecting your equipment, configuring your workflows, and supporting your operation long after go-live.
Find out where your production time is actually going.
See downtime as it happens, understand what is driving it, and focus your team on the losses that matter most.