Robot performance
Robot repeatability under load: the spec versus the measurement
A robot arm rated for plus or minus 0.1 mm repeatability measured about 0.2 mm of spread under a 16 kg load, past its own specification.
The figure comes from a study that measured positioning accuracy across loads of 6, 10, and 16 kg. At 6 kg the arm sat comfortably inside spec; at 16 kg the range on two axes reached roughly 0.2 mm, double the rated figure.
This page traces the measurements to the study and makes a narrow, useful point: a repeatability spec is a single condition, and the number you actually get depends on the payload.
Data covers Measured positioning study of a modular industrial arm under varying loads (2025). Last reviewed by a human editor before publication.
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 |
|---|---|---|---|---|
| plus or minus 0.1 mm | Rated repeatability | [A] | High | The arm's datasheet repeatability specification. A single number, quoted as if it held across all conditions. |
| 0.0879 mm | Measured range at 6 kg (worst axis) | [A] | Medium | At a 6 kg load the measured range on the worst axis stayed inside the 0.1 mm spec. Light loads meet the datasheet. |
| about 0.2 mm | Measured range at 16 kg | [A] | Medium | At 16 kg the range on the Z and Y axes reached about 0.2 mm, roughly double the rated repeatability. Heavy loads exceeded spec. |
| 6, 10, and 16 kg | Loads tested | [A] | High | The study measured across three payloads, which is what let it show accuracy changing with load rather than reporting one condition. |
Why the numbers disagree
A datasheet repeatability figure is measured under specific, favorable conditions, usually a light or nominal load. The study shows why that matters: the same arm that met its plus or minus 0.1 mm spec at 6 kg spread to about 0.2 mm at 16 kg. The spec is not wrong; it is just narrow.
Repeatability and payload are linked because a heavier load deflects the arm and its joints more, and loads the drivetrain harder. So the number a robot delivers in a real cell depends on how close the application runs to the rated payload, not just on the headline spec.
This is one arm in one study, a modular industrial robot, so the exact figures are specific to it. The general point, that measured accuracy degrades toward and past spec as load approaches the maximum, is the transferable lesson, not the precise 0.2 mm.
How to cite these figures
Read a repeatability spec as a best-case, light-load figure, and expect degradation as the payload approaches the rated maximum.
If accuracy matters in your application, cite the measured behavior: this arm held spec at 6 kg and roughly doubled its spread at 16 kg, and plan for margin rather than assuming the datasheet number under full load.
Treat the exact 0.2 mm as specific to the tested arm. The transferable claim is directional: heavier load, worse repeatability.
Where people go wrong
Assuming the datasheet repeatability holds at full payload. It is typically a light-load figure and degraded to about double here at 16 kg.
Generalizing the exact numbers to any robot. They are one modular arm in one study; the direction transfers, the values do not.
Ignoring payload when specifying for accuracy. Running near the rated maximum is where repeatability erodes.
How we checked
The figures come from a peer-reviewed positioning-accuracy study that measured a modular industrial arm under three loads. We accessed it through PubMed Central and confirmed the plus-or-minus-0.1 mm spec, the 0.0879 mm range at 6 kg, the roughly 0.2 mm at 16 kg, and the tested load set in its text.
We frame it as a single measured study whose value is the load comparison: measuring at 6, 10, and 16 kg is what reveals accuracy changing with payload, something a single-condition test would miss.
The precise numbers belong to the tested arm. We state the transferable finding, repeatability degrades as load approaches the maximum, and hold the exact values to their source rather than presenting them as universal.
Full source list
Primary sources, with live links. Every figure above traces to one of these.
- [A]PMC (PubMed Central)2025
"Study of Positioning Accuracy Parameters in Selected Configurations of a Modular Industrial Robot, Part 1", PMC (PubMed Central)
https://pmc.ncbi.nlm.nih.gov/articles/PMC11722867/
Common questions
- Does a robot always hit its repeatability spec?
- Not under all loads. A study of a modular arm rated at plus or minus 0.1 mm found it held spec at 6 kg but spread to about 0.2 mm at 16 kg, roughly double the rated figure.
- Why does load affect repeatability?
- A heavier payload deflects the arm and joints more and loads the drivetrain harder, so the position the robot returns to varies more. Accuracy erodes as the load approaches the rated maximum.
- Do these numbers apply to any robot?
- No. They are one modular arm in one study. The direction, worse repeatability under heavier load, transfers; the exact 0.2 mm does not.
- How should I specify a robot for accuracy?
- Treat the datasheet repeatability as a light-load best case, plan for degradation near the rated payload, and leave margin rather than assuming the headline number under full load.
More data, traced to source
- Robot reliability numbers: the vendor claims and the one independent study
Manufacturers advertise robot uptime in the high nineties and mean time between failures in the tens of thousands of hours. The one independent study of more than 400 factories found a robot cell is reliable 88 percent of the time, with 87 minutes between failures.
- 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.
- A cobot's measured productivity gain: 10%, not a multiple
Collaborative-robot marketing implies large throughput gains. A time-studied assembly cell measured the actual gain at 10%. Here is the study, and why a measured number beats a marketed one.