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Humanoid hard sell: Building robots for the manufacturing age
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Scarlett Evans

· 1 min read

BusinessAI Business

Humanoid hard sell: Building robots for the manufacturing age

Q5D's Q25 5-axis wiring-automation robotQ5D

Where humanoid publicity outpaces reality, why purpose-built machines deserve more attention and how the West can get automation onto the factory floor.

As humanoids move out of the lab and into real-world deployment, some caution that excitement about their capabilities may be outpacing reality.

Stephen Bennington, CEO of British robotics company Q5D, says that with industry deployments, manufacturers shouldn't assume copying the human worker is the best way to automate a job. His advice is to start with the process rather than the robot: when a task isn't tied to human-built environments, a purpose-built machine can be faster, more accurate and significantly cheaper.

In this Q&A, Bennington discusses where humanoid robotics stands, how AI is changing industrial automation and what Western manufacturers can learn from China.

There is a huge amount of excitement about humanoid robots at the moment. Where does the technology genuinely stand, and where is the publicity getting ahead of reality?

Stephen Bennington: The progress is exciting. Humanoid robots are becoming more capable, and we are starting to see trials in industrial environments rather than just impressive demos. But for many applications, I do think the hype is still ahead of reality.

There is, of course, a logical reason for the interest. Our factories, warehouses and tools were designed around people. So, if you can build a robot that can move through those environments and interact with the same equipment, you potentially avoid having to redesign the workplace around the machine.

However, where I would be slightly more cautious is the assumption that copying the human operator is always the best way to automate a job.

Rather than starting with the robot, manufacturers should start with the process -- looking closely at what they are trying to automate and the most effective way of doing it.

Are there any particular approaches to address these challenges?

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This story was published by AI Business and written by Scarlett Evans. SyncAI.news shows a preview; the complete article is on the publisher's site.

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