In 1913, Henry Ford revolutionized car-making with the first moving assembly line, an innovation that made piecing collectively new autos quicker and extra environment friendly. Some hundred years later, Ford is now utilizing synthetic intelligence to eke extra velocity out of at present’s manufacturing strains.
At a Ford Transmission Plant in Livonia, Michigan, the station the place robots assist assemble torque converters now features a system that makes use of AI to study from earlier makes an attempt easy methods to wiggle the items into place most effectively. Inside a big security cage, robotic arms wheel round greedy round items of steel, every about the diameter of a dinner plate, from a conveyor and slot them collectively.
Ford makes use of know-how from a startup referred to as Symbio Robotics that appears at the previous few hundred makes an attempt to find out which approaches and motions appeared to work finest. A pc sitting simply exterior the cage exhibits Symbio’s know-how sensing and controlling the arms. Toyota and Nissan are utilizing the identical tech to enhance the effectivity of their manufacturing strains.
At a Ford plant in Livonia, Michigan, robots assemble torque converters by wiggling elements into place, with some assist from machine studying.
Courtesy of Symbio
The know-how permits this a part of the meeting line to run 15 % quicker, a major enchancment in automotive manufacturing the place skinny revenue margins rely closely on manufacturing efficiencies.
“I personally suppose it’s going to be one thing of the future,” says Lon Van Geloven, manufacturing supervisor at the Livonia plant. He says Ford plans to discover whether or not to make use of the know-how in different factories. Van Geloven says the know-how can be utilized wherever it’s attainable for a pc to study from feeling how issues match collectively. “There are many these purposes,” he says.
AI is commonly considered as a disruptive and transformative know-how, however the Livonia torque setup illustrates how AI could creep into industrial processes in gradual and sometimes imperceptible methods.
Automotive manufacturing is already closely automated, however the robots that assist assemble, weld, and paint autos are primarily highly effective, exact automatons that endlessly repeat the identical job however lack any capacity to know or react to their environment.
Including extra automation is difficult. The roles that stay out of attain for machines embody duties like feeding versatile wiring by way of a automotive’s dashboard and physique. In 2018, Elon Musk blamed Tesla Mannequin 3 manufacturing delays on the choice to rely extra closely on automation in manufacturing.
Researchers and startups are exploring methods for AI to provide robots extra capabilities, for instance enabling them to understand and grasp even unfamiliar objects transferring alongside conveyor belts. The Ford instance exhibits how current equipment can typically be improved by introducing easy sensing and studying capabilities.