Robot performance
A cobot's measured productivity gain: 10%, not a multiple
A cobot improved productivity by 10% in a time-studied assembly cell, not the large multiples the marketing implies.
The number comes from a peer-reviewed process-time study that compared a manual assembly of a mechanical joint against the same assembly with a collaborative robot, using standardized time measurement. The manual cycle took 25.768 seconds; the cobot cell took 23.166, a saving of 2.603 seconds, or 10%.
This page traces the 10% to its study and is clear that it is one measured task, offered against the habit of quoting cobot productivity in vague multiples.
Data covers Time-and-motion study of a collaborative assembly task (2022). 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 |
|---|---|---|---|---|
| 2.603 s, or 10% | Measured productivity gain | [A] | Medium | The measured productivity gain from adding a cobot to the assembly task, from a standardized time study. One task, one study. |
| 715.8 TMU | Manual assembly cycle | [A] | Low | The manual cycle time in Time Measurement Units, equivalent to 25.768 seconds. The baseline the cobot was measured against. |
| 653.5 TMU | Cobot assembly cycle | [A] | Low | The cobot cycle time, equivalent to 23.166 seconds. The difference from the manual cycle is the 10% gain. |
Why the numbers disagree
Marketing and measurement describe cobot productivity on different scales. Vendor language leans on multiples and dramatic before-and-after gaps; the measured study found a 10% improvement on a real assembly task. A 10% gain can be worth having, but it is not the order-of-magnitude story a sales deck implies.
The method is what gives the number weight. The study used standardized time measurement to compare a manual assembly against the same assembly with a cobot, so the 10% is a like-for-like process-time result, not an estimate or a projection. That is rarer than it should be in cobot productivity claims.
The honest caveat is scope. This is one task, one cell, one study. A different task with more waiting, more repetition, or a worse manual baseline could show a larger gain, and a well-optimized manual process could show less. The value is a measured anchor, not a universal figure.
How to cite these figures
Cite the 10% as a measured process-time gain from a specific assembly study, not a general cobot productivity figure.
Pair it with the caveat that gains are task-specific: a cobot helps most where the manual process has waiting or awkward handling, and least where the manual baseline is already tight.
When you see a cobot productivity multiple, ask for the method. A measured 10% with a time study beats an unmeasured 3x every time.
Where people go wrong
Generalizing the 10% to all cobot applications. It is one measured task; other tasks will differ.
Comparing it directly with a vendor multiple. The vendor figure usually has no method; the 10% is a like-for-like time study.
Reading 10% as disappointing or as impressive without context. Whether it pays depends on volume, labor cost, and the specific task.
How we checked
The figure comes from a peer-reviewed process-time study of a collaborative assembly task. We retrieved it through the PubMed Central mirror, because the journal's own page blocks automated verification, and confirmed the 2.603-second, 10% gain and the manual and cobot cycle times in its text.
We present it as a single measured study and rate it accordingly. Its strength is the standardized time-measurement method, which makes the comparison like-for-like; its limit is that one task cannot stand in for every cobot deployment.
We did not find a broad, independent dataset of measured cobot productivity gains. Absent that, a well-documented single study is the most defensible anchor, and the page says so plainly.
Full source list
Primary sources, with live links. Every figure above traces to one of these.
- [A]PMC (PubMed Central) mirror of Materials (MDPI)2022
Faccio et al., "Evaluation of Collaborative Robot Sustainable Integration in Manufacturing Assembly by Using Process Time Savings" (Materials, MDPI), PMC mirror
https://pmc.ncbi.nlm.nih.gov/articles/PMC8781979/
Common questions
- How much does a cobot improve productivity?
- In a time-studied assembly task, the measured gain was 10%. That is a real, like-for-like result, and far more modest than the multiples cobot marketing tends to imply.
- Is 10% the gain for every cobot?
- No. It is one measured task in one study. Gains are task-specific: larger where the manual process has waiting or awkward handling, smaller where the manual baseline is already tight.
- Why trust 10% over a vendor's bigger number?
- Because the 10% comes from a standardized time study comparing the same assembly with and without a cobot. Most vendor multiples come with no method to check.
- Is a 10% gain worth it?
- It depends on volume, labor cost, and the task. A 10% cycle-time saving can pay off at high volume and not at low; the figure is an anchor, not a verdict.
More data, traced to source
- Do robots boost productivity? US manufacturing productivity says not lately
Robots are sold on productivity. US manufacturing labor productivity growth went from 3.4% a year to negative over the era automation accelerated. The measured record does not show the promised surge.
- 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.
- The cobot study where output fell and posture improved
In a controlled study, workers made fewer products with a collaborative robot than without one, 5.35 versus 8.03. What improved was their posture. A measured counterexample to the cobot productivity pitch.