Ford’s increasingly intelligent robots are accelerating the assembly line

1913, Henry Ford revolutionized car manufacturing the first mobile assembly line, an innovation that has made new vehicles work together faster and more efficiently. One hundred years later, Ford is being used Artificial intelligence to get a higher speed to the present manufacturing lines.

At Ford Transmission Plant In Livonia, Michigan, the station that helps robots assemble moment converters has a system that uses AI to learn how to move parts more efficiently from previous attempts. Inside a large safety cage, the robot’s arms catch circular metal pieces on the wheel, each the diameter of a food plate, from a conveyor and into them together.

Ford uses startup technology called Symbio Robotics which looks at the last hundreds of attempts to find out which approaches and movements work best. The computer sitting outside the cage shows how Symbio’s technology detects and controls the arms. Toyota and Nissan they are using the same technology to improve the efficiency of their production lines.

The technology allows this part of the assembly line to run 15 percent faster, a significant improvement in automotive manufacturing, where small profit margins depend on manufacturing efficiency.

“I personally think it will be something for the future,” says production director Lon Van Gelov of the Livonia plant. He says Ford plans to study whether it wants to use the technology in other factories. Van Geloven says that technology can be used anywhere because it is possible to learn from computers how to feel things fit together. “There are a lot of those apps,” he says.

AI is often seen as a disruptive and transformative technology, but the configuration of Livonia’s momentum shows how AI can enter industrial processes in a gradual and often imperceptible way.

Automotive manufacturing is already highly automated, but robots that help assemble, weld, and paint vehicles are essentially precise and powerful automations that continually repeat the same task but lack the ability to understand or react to the environment.

Adding more automation is a challenge. Work that is not available to machines includes work such as feeding flexible cables through the car’s controls and bodywork. In 2018, Elon Musk blamed delays in production of the Tesla Model 3 the decision to focus more on automation in manufacturing.

Researchers and startups are exploring ways to make robots more capable of AI, for example by enabling them perceive and detect unknown objects moving along with the conveyor belts. Ford’s example shows how existing machinery can be improved by introducing simple detection and learning capabilities.