oceanplayer

Oceanplayer Industrial Laser Equipment | Cleaning, Welding, Marking, Automation Sample Testing | Free Engineering Tools | Global Shipping
Main Systems
Best Seller Oceanplayer 500W pulsed laser cleaning machine
Featured Model
500W Pulsed Laser Cleaner

Higher pulse cleaning speed with controlled surface impact.

500W PulsedFine ControlBest Seller
Engineering Tools
Applications
Industries
Company
Resources

Cobot Adoption Rate by Industry

Cobots accounted for 11.9% of new industrial robot installations worldwide in 2024, according to IFR’s 2025 release. That measures robot units, not the percentage of companies using cobots. The public sources reviewed here do not provide comparable global adoption rates for each industry, so industry installation data and application examples need to be read separately.

Universal Robots arm and gripper over a conveyor in a manufacturing education lab
A cobot demonstration in a manufacturing education lab. Photo: COD Newsroom / Wikimedia Commons, CC BY 4.0. Uncropped.

What does “cobot adoption rate” measure?

A collaborative robot, or cobot, is designed with capabilities intended to support collaborative applications. Its installation does not necessarily mean a person works beside it during every cycle. If the equipment category is unfamiliar, start with how a collaborative robot works.

Before comparing a percentage, identify its denominator, location and measurement year. Four common metrics answer different questions:

Share of new robot installations
Cobots installed during a year divided by all industrial robots installed in that year. This is the basis of IFR’s global cobot share.
Share of adopting sites or companies
Sites or companies operating at least one cobot divided by the population studied. One business can own many sites, so even these two denominators differ.
Installed stock
Robots already in operation at a point in time, accumulated across installation years. A large installed base can coexist with a slow year for new purchases.
Survey intent
Respondents considering, budgeting for or piloting cobots. The survey stage and sample matter; stated intent does not establish production use.

Illustrative example: if 20 of 100 surveyed factories operate a cobot, site adoption in that sample is 20%. It does not tell you how many robot units those factories bought, how many cobots they own, or whether the sample represents their entire industry.

Global cobot installations reached 64,542 in 2024

Annual worldwide installations. Scroll the table on a small screen.

Data yearCobot unitsShare of new industrial robots
202141,7297.9%
202257,96610.5%
2023, revised57,14810.6%
202464,54211.9%

Source: IFR World Robotics 2025 press presentation, slide 12. The 2023 figures are marked as revised in this release.

The series shows a higher cobot share in 2024 than in 2021, with little change in unit volume between 2022 and 2023. Growth therefore was not a smooth increase every year.

The 2025 release revised the earlier 2023 benchmark of 57,040 units and 10.5%. Keep a trend series on a consistent release basis rather than combining older and revised figures.

For 2024, 64,542 cobots divided by 542,076 total industrial robot installations gives about 11.9%. It does not mean 11.9% of factories, workers or manufacturing tasks use cobots. IFR executive summary.

Data status, checked 10 September 2026: these are completed 2024 results published in 2025. IFR’s June 2026 presentation labels its 2025 results preliminary and schedules the final World Robotics 2026 release for 24 September 2026. The two series are kept separate here. IFR publication schedule and preliminary-data note.

Which industries lead overall robot installations?

Electrical/electronics, automotive, and metal and machinery were the three largest customer groups for new industrial robots in 2024. The chart includes conventional and collaborative robots together. It establishes the scale of industrial automation in each sector, without establishing a cobot-only industry ranking.

2024 new industrial robot installations worldwide — all robot types

Electrical / electronics128,899
Automotive126,088
Metal / machinery88,777
Plastic / chemical products26,491
Food / beverage20,792
All other industries77,752
Industry unspecified73,277
Common bar scale: 0–150,000 units. All seven groups total 542,076 installations. “All other” and “unspecified” are included to show the full denominator. Source: IFR World Robotics 2025 executive summary, customer-industry chart.

A sector can install many robots because it contains large plants with extensive conventional automation. That does not show what fraction of its businesses use a cobot. Ranking “fastest cobot adopters” would require comparable cobot-specific observations by industry over time.

Where are cobots used in different industries?

IFR identifies automotive, electronics, aerospace, consumer goods, pharmaceuticals and logistics among cobot users. It also describes applications such as machine tending, welding and palletizing. The examples below help identify a task to investigate; they are not measured adoption rates or a maturity ranking. IFR’s overview of collaborative robot applications.

Scroll horizontally on mobile to compare application limits.

IndustryTasks to evaluateWhat can limit the application
Automotive and suppliersFastening, part presentation, inspection, machine tending and selected assembly operations.Required line rate, tool and workpiece hazards, fixture variation, and recovery from a missed part.
Electronics and precision assemblyScrewdriving, test-fixture loading, dispensing and tray handling.Small-part presentation, placement tolerance, electrostatic-discharge controls and test-system interfaces.
Metalworking and machineryCNC loading, welding, inspection and selected finishing operations.Machine interlocks, workholding, sharp or hot parts, fumes and dust. A repetitive path does not solve variable fit-up.
Plastics and consumer productsMolding-machine tending, insert handling, inspection and packing.Hot components, gripping delicate parts, product changeovers and the machine’s safe access sequence.
Food and beverageCase handling, end-of-line packing and palletizing.Box stability, peak line rate and stack height. Direct food contact adds hygiene and material requirements beyond handling sealed cases.
Logistics and warehousingKitting, tote handling, palletizing and selected picking tasks.Object variety, grasp reliability, reach, peak demand and conveyor or warehouse-system integration.
Pharma, medical devices and laboratoriesInstrument tending, sample or tray handling, inspection and packaging.Cleaning compatibility, contamination control, documentation and process validation for the specific environment.

Keep the robot category consistent. Warehouse autonomous mobile robots, or AMRs, are not automatically counted as collaborative industrial arms. Robots used for patient treatment also differ from manufacturing or laboratory automation. For the warehouse distinction, see cobots versus AMRs.

Why adoption differs within the same industry

Task repeatability and integration capacity

Two factories in the same sector can have very different projects. One may present parts in fixed trays; another may need a robot to find oily, tangled or easily damaged parts. The second task adds sensing, gripping and recovery work even if the robot arm is identical.

NIST’s integration guide considers process variation, manipulation difficulty, precision and integration complexity when selecting a workcell. This helps explain why a familiar industry label is less useful than a clear process description. NIST AMS 100-41, sections 2–3.

High product mix can make retasking valuable, but fixtures, grippers, programs and checks still need a workable changeover method. The team must also be able to maintain the cell and recover from routine faults.

Throughput, access and the complete application

Collaborative features do not remove the need to evaluate the tool, payload, surrounding equipment and human tasks. Protective measures can change the achievable cycle time and the space required around a cell.

ISO 10218-2:2025 addresses industrial robot applications and cells, including their integration and operation. A cobot carrying a welding torch, sharp tool or heavy part needs an application-specific safety design. ISO 10218-2:2025 scope.

Compare the production rate under the intended protective measures. Where high speed and physical separation suit the task, conventional automation may also be worth evaluating. The relevant question is how the complete cell performs in use.

2020 palletizing cell illustration showing robot arm, gripper, conveyor, operator controls, mobile frame and lift column
A 2020 palletizing-system example shows how the arm depends on gripping, material supply, controls and positioning hardware. Labels describe the pictured configuration. CollaborativePalletizer / Wikimedia Commons, CC BY-SA 4.0. Uncropped; select the image for a larger view.

What one documented adoption case shows

NIST MEP’s July 2024 story describes AMG Industries, an automotive supplier facing workforce and productivity constraints. The company trialed a loaned collaborative robot on a repetitive exhaust-tip production task, with support from MEP engineers.

200 → 276parts per hour reported in the trial
38% higher output

The report says workers were redeployed to other areas and, after a three-month trial, AMG purchased its own UR10e for the task. It is a specific application result, not an automotive-industry average. Read the NIST MEP case.

What to take from the case: a defined repetitive task, a measured manual baseline and on-site integration support made the trial assessable. A different part family, staffing pattern or bottleneck would need its own evidence before claiming a similar gain.

How to use adoption data in a plant-level decision

Use market data to understand the technology’s scale and find relevant application examples. Then compare candidate tasks inside your own operation. A practical first assessment should answer three questions:

  1. What recurring loss will the cell address? Measure accepted output, manual touch time, staffing gaps, quality losses and changeover effort. Choose a task with sustained demand and a benefit that the business can actually use.
  2. What must work around the arm? Define part presentation, tooling, machine communication, protective measures and exception recovery. Test representative parts and difficult variants before committing to a complete cell.
  3. What will count as a successful deployment? Set targets for accepted output, quality, operator involvement, recovery and installed cost. Include integration, training, maintenance and realistic utilization in the business case.

Freed operator time is not automatically a cash saving, and extra capacity has value only when production demand can use it. For the cost breakdown, see the cobot cost and ROI guide. For project stages and dependencies, see the cobot deployment timeline.

Discuss a defined automation task

Send Oceanplayer Laser the part photos, process sequence, payload, cycle target, product variation and available floor space. These details make a welding or handling application review more useful than an industry adoption percentage alone.

Discuss an automation application

Sources and data scope