Automotive
Assembly, screwdriving and inspection next to people, on lines with many vehicle variants.
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Link to the SDGs SDG 8 SDG 9
- SDG 8 Decent work and economic growth Cobots can take over repetitive tasks and hard postures, such as working with arms above the head, reducing the risk of injury.
- SDG 9 Industry, innovation and infrastructure Shows how sensors and simulation help assembly lines handle many variants without stopping production.
Written with AI assistance. Still under review by the team.
The automotive industry was one of the first to use industrial robots at scale — usually fenced off, in welding and painting. Cobots fill a different space: final assembly, where people still do most of the work and each car may have a different combination of options.
Why cobots here
- Repetitive, tiring tasks: driving dozens of identical screws, laying adhesive beads, holding parts in awkward positions.
- Working side by side: the cobot does the repetitive part and the person does what needs dexterity, judgment or visual checks.
- Fast changeover: with many variants per line, a robot that is easy to reprogram and relocate is valuable.
Where IoT and the digital twin come in
- Traceability: the screwdriver and the cobot record the torque and angle of every screw, linked to the vehicle number.
- Cell simulation: before changing the line, the digital twin lets you test reach, cycle time and the split of tasks between person and robot.
- Maintenance: vibration and current sensors on tools help spot wear before a failure.
Watch out for
- Payload: the weight of the part plus the gripper must fit the cobot’s capacity, with margin.
- A dangerous tool makes a dangerous application: a cobot holding a cutting tool, hot glue or a sharp tip is not “safe because it is a cobot”. Every cell needs a risk assessment under the robot safety standards (the ISO 10218 series, and ISO/TS 15066 for collaborative applications).
- Speed: to work near people, cobots usually run slower. That has to be part of the cycle-time calculation.