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How Tesla delivered enough Model 3s in Q4 2019

Xiao Zhong, Ph.D., Analyst
February 13, 2020

Tesla finally delivered enough Model 3s in Q4 2019, but it teaches Elon Musk (and us) a lesson on automation

Tesla went through production hell in 2018, thanks to constant delays of the Model 3 shipments. Elon Musk admitted these delays were partly due to the company's overly deployed robotic assembly systems, among many other reasons. 

In early 2017, Tesla acquired industrial robotics company Perbix and began integrating its robotic assembly systems into the Tesla factory. However, to save Tesla from the production mayhem, Musk had to remove some of them in 2018 and hire more human mechanics to deliver the Model 3. That strategy, along with many other actions, enabled the company to deliver more Model 3s than promised in Q4 2019.

There is no doubt that Tesla's production success in Q4 can be attributed to Musk and the company's strong drive and ability to execute, not to mention the fact that they work tirelessly to get things done. However, this case serves as a good counter case against "more automation, faster." Tesla used to (still does) consider its high degree of automation a powerful weapon, but it may not consider how to deploy its "weapon" wisely to avoid overkill.

Automation does not always give a higher production throughput. In this case, the product is too complex for a high degree of automaton to be efficient (at least for now), so it actually slows down the process. Just as Musk said, the better strategy would be to introduce automation in stages. Collaborative robots, working side by side with human workers, can always be an intermediary step.

We live in the age of digitalization and automation, and it seems very intuitive to introduce more automation and think that will improve efficiency. While it may be true in some cases where processes of product manufacturing are simple enough to be fully automated, like food packaging, for example, in most cases, product manufacturing (automotive, aerospace, and medical devices are some good examples) is still too difficult for robots to fully take over, and creating a human/robot interactive environment is a more realistic step. 

 

 

 

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