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Mercedes Benz is kicking Robots Off the Assembly Line

Due to the success of the Mercedes-Benz S-Class, the robots are getting overworked and are not able to keep up with demand. As a result, humans are appearing back on the assembly lines, and this is something that was not expected.

Daniel Okafor
Daniel OkaforSenior AI Reporter
1 min read
Mercedes Benz is kicking Robots Off the Assembly Line

Due to the success of the Mercedes-Benz S-Class, the robots are getting overworked and are not able to keep up with demand. As a result, humans are appearing back on the assembly lines, and this is something that was not expected. The reason is that robots are not flexible enough according to the head of production Markus Schaefer who added that it is also cost effective and will ensure that the company continues to be successful.

All this is taking place in the plant at Sindelfingen, and while there are some of the top of the range models produced here, it is an old site but still manages to produce over 400,00 cars a year. The robots have worked successfully when it comes to repetitive actions, but less suitable when adaptation was needed.

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The hope is that the time required to produce a car will be cut from 61 to 30 hours, and robots can’t deal with the change needed. Humans back on the line are enabling the company can shift a line of production over a weekend rather than spend weeks reprogramming the robots to allow them to work to the new pattern. This prevents the down time that has previously been suffered.

The new E-Class will see a human worker replacing, at least, one of the robots that have previously worked on it and although the robots are not going to be permanently removed from the production line, they need to become smaller and more flexible.

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Daniel Okafor

Daniel Okafor

Senior AI Reporter

Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.

All stories by Daniel Okafor (316)