Robotics reliability
Robot reliability numbers: the vendor claims and the one independent study
A robot cell runs 88% of the time. The other 12% is where the money goes, and most of it is not the robot's fault.
That comes from the one published study that measured real robot cells across more than 400 factories. The same study puts the mean time to failure of a cell at 87 minutes, a world away from the reliability pitch on a spec sheet, where mean time between failures is quoted in the tens of thousands of hours.
This page traces both sets of numbers to where they actually come from, so you can tell a measured statistic from a sales figure.
Data covers vendor MTBF claims against the 2019 review of 400-plus factory reliability data. Published 2026-07-14. Last reviewed 2026-08-16. Last updated 2026-08-16. Edited by Mike Ramsey / Reliable Media.
The figures and where they come from
Each figure is rated for how safely you can cite it today. Ratings judge current usability, not whether a number was ever correct.
| Figure | What it is | Source | Citation Confidence | Notes |
|---|---|---|---|---|
| 88% reliable | Average robot cell reliability | [A] | High | The average reliability of a robot cell across the study's factories. It is the headline finding and the number to cite for real-world robot uptime. |
| 12% stopped | Share of time the cell is stopped | [A] | High | The flip side of 88 percent reliability. The cell is not working 12 percent of the time. |
| 87 minutes | Mean time to failure, robot cell | [A] | High | Mean time to failure for a robot cell. Compare it with the vendor MTBF claims measured in tens of thousands of hours. |
| 400+ factories | Factories in the study | [A] | High | The study drew on data from more than 400 factories, which is what makes it the credible independent source here. |
| 80% not the robot | Downtime not caused by the robot | [A] | Medium | Of the time a cell is down, 80 percent is caused by problems the study calls not related to the robot itself, naming conveyors, faulty sensors, and paint guns. Reliability is a cell property, not a robot property. |
| 40,000 to 100,000 hr | Advertised MTBF (vendor claim) | [A] | Low | The range of MTBF figures vendors advertise, as listed in the source (40,000, 60,000, 80,000, and 100,000 hours). These are spec-sheet and certification claims with no independent verification. Do not cite them as measured reliability. |
Why the numbers disagree
The two kinds of numbers measure two different things. A vendor MTBF figure describes a single robot arm running under controlled conditions. The 88 percent reliability figure describes a whole robot cell in a real factory, including its tooling, fixtures, sensors, and the parts flowing through it.
That distinction is the whole story. The study found that 80 percent of the time a cell stops, the cause is not the robot. So a robot can be genuinely reliable as a component and still sit inside a cell that is down 12 percent of the time. Vendors quote the component number; the plant lives with the cell number.
The vendor figures also have no published methodology behind them. The source lists advertised MTBF values of 40,000, 60,000, 80,000, and even 100,000 hours, and notes that some claims now imply a robot will run 43 years before it fails. None of those are tied to a dataset anyone can inspect.
How to cite these figures
For a realistic figure on how often a robot cell is actually running, cite the 88 percent reliability and 87 minute mean time to failure from the study of more than 400 factories, and name the source.
Treat any MTBF figure in the tens of thousands of hours as a vendor claim, not a measurement. If you must use one, attribute it to the manufacturer and make clear it describes the arm, not the cell.
When you talk about uptime, say whether you mean the robot or the cell. The gap between them is most of the argument, and mixing them is how a 99 percent robot ends up inside an 88 percent cell.
Where people go wrong
Quoting a vendor MTBF as if it were measured uptime. An 80,000 hour MTBF is a controlled-condition claim about the arm, not evidence that a cell runs 80,000 hours between stops.
Reading 88 percent reliability as the robot being broken 12 percent of the time. Most of that downtime is not the robot. The study names conveyors, sensors, and paint guns.
Assuming there is a large body of independent robot-reliability data. There is very little. The figures here come from effectively one published study, set against vendor MTBF claims that no comparable independent study tests.
How we checked
Every figure on this page is drawn from a single fetchable primary source: The Robot Report's 2019 article, which reports reliability research published in the International Journal of Performability Engineering. We fetched the article and confirmed each figure appears in its text before publishing.
We went looking for a broader base of independent robot-reliability data and did not find one. The underlying journal article sits behind a paywall, and the vendor MTBF and uptime figures trace only to spec sheets and marketing pages, none of which publish a method. Where a number could not be tied to a free primary source, we labelled it a vendor claim rather than a measurement.
The Citation Confidence rating reflects how safely a figure can be quoted today. The measured study figures rate High. The advertised MTBF and the 43-year claim rate Low, because they are marketing figures with no verifiable basis, included here only to show what the study was responding to.
Full source list
Primary sources, with live links. Every figure above traces to one of these.
- [A]The Robot ReportJune 3, 2019
The Robot Report (Steve Sickler, Tend.ai), reporting reliability research published in the International Journal of Performability Engineering
https://www.therobotreport.com/the-fake-news-about-robots-and-their-reliability/
Common questions
- What is the real uptime of an industrial robot?
- The one independent study of more than 400 factories found the average robot cell is reliable 88 percent of the time, so it is stopped about 12 percent of the time. That is a cell figure. A single robot arm on its own is more reliable, but the cell is what a plant actually runs.
- Are the 80,000-hour MTBF figures real?
- They are vendor claims with no published methodology. The source lists advertised figures of 40,000 to 100,000 hours and treats them as marketing, not measurement. There is no independent dataset behind them.
- Why does a reliable robot still cause downtime?
- Because most cell downtime is not the robot. The study found that 80 percent of the time a cell stops, the problem is not related to the robot, and names conveyors, faulty sensors, and paint guns as the sort of thing it is instead.
- What is mean time to failure for a robot cell?
- The study reported 87 minutes for a robot cell. That is far shorter than the hours-based MTBF vendors advertise, because it measures the whole cell in a real factory rather than the arm alone.
More data, traced to source
- Robot workplace deaths: what the public record does and doesn't show
The figure of about 41 US robot-related deaths is quoted widely, but it cannot be verified through any free primary source, and the same agency has published two different totals. This page traces what is and is not documentable about robot workplace fatalities.
- What a robotics technician actually earns, and why the wage is hard to find
There is no federal wage line for a robotics technician. The government folds the job into a broader category with a median near $73,900 a year. This page shows where that number comes from and what it does and does not cover.
- Robot density statistics and where they come from
The most-cited robot density figures are stale. Here are the current numbers, where each one comes from, and why the global average fell while automation kept rising.
- Do robots really run 24/7? The measured runtime is far lower
The pitch is that robots run around the clock. The best measured data on manufacturing machine runtime shows a median of 32% and a weighted average of 54.5%. The 24/7 figure is a ceiling, not a norm.
- Do cobots pay back in 195 days? Tracing the number everyone quotes
The figure that cobots pay for themselves in 195 days is quoted across the industry. It traces to Universal Robots' own marketing, based on customer data it has not published a method for. Here is the trail.
- How much energy does an industrial robot use? Mostly overhead
Two measured studies of industrial arms found that overhead, electronics and brakes and holding position, dominates power draw, and that less than 2.5% of the energy consumed becomes useful mechanical work. The numbers vendors do not publish.
- Robot repeatability under load: the spec versus the measurement
A robot arm rated at plus or minus 0.1 mm repeatability measured worse under load, with the spread reaching about 0.2 mm at 16 kg. The datasheet is one number; the measured accuracy depends on what the robot is carrying.
- A robot's repeatability is not its accuracy: the measured gap
A robot's repeatability spec is a sub-millimeter number; its actual accuracy out of the box is far worse. In one measured study a high-precision arm was off by 1.7730 mm before calibration, and calibration cut that to 0.1041 mm.
- How long does an industrial robot last? The 12-year figure is a guess
The widely repeated 'robots last about 12 years' is not a measurement. It is the bookkeeping assumption the IFR uses to estimate the robot population, and the IFR itself calls the uncertainty, 5 versus 12 versus 15 years, substantial.
- The '$260,000 an hour' downtime figure: who actually said it?
The claim that manufacturing downtime costs $260,000 an hour is everywhere. Trace it and the carriers agree on the source, Aberdeen Research, but none of them link or date it, and they cannot agree on whether it is an average or a worst case.
- Preventive versus predictive maintenance: what the savings actually are
The US Department of Energy puts predictive maintenance at 8% to 12% cheaper than preventive, and preventive at 12% to 18% cheaper than reactive. Other government estimates of maintenance cost disagree by a factor of four.