The rise of the connected, automated factory goes by many names: the industrial internet, the internet of things, and the fourth industrial revolution (industry 4.0). Technology is enabling levels of industrial automation few could have imagined when the first hulking industrial robots were introduced to automotive factories in the early 1960s.
A 2013 Oxford University study suggested nearly half of US employment has a strong probability of being supplanted by machinery and computerization within the next decade or two. There’s no denying that machines now do a host of jobs that were once performed by humans, and that trend will continue. But as the drive toward ever-greater efficiency and product quality has increased automation, some in the auto industry are beginning to rethink how industrial robots fit into the picture.
For years robots have been good at doing the literal heavy-lifting portion of auto manufacturing. Robots excel at things requiring a complex combination of pinpoint accuracy and brute strength, like stamping, forming, welding, and positioning heavy and large metal components. Such machines are large and heavy themselves, and working in their proximity can be dangerous for humans. The robots usually work in enclosed, caged environments to protect their flesh-and-bone co-workers.
As robotic technology has advanced, the robots in automobile manufacturing remain mostly stuck on the front end of the assembly process. Large numbers of light-vehicle models, and niches and options within those models, make for a lot of variables in terms of assembly. So as a car moves further down the assembly line, the cost efficiency of using robots has tended to drop as the need for a thinking worker increases. The costs of building a robot with enough sensors and intelligent computer learning algorithms start to hit a point of diminishing returns.
The collaborative robot, or “co-bot,” may be the key to bridging the gap. Co-bots have gradually begun to enter the assembly line environment to work in concert with human workers. Audi is testing a collaborative robot that hands parts to a human co-worker who installs them. Volkswagen is using a similar system to aid in powertrain preassembly. In many cases, as with a Ford factory in Germany, the co-bot does the heavy lifting and fitting of parts while the human ensures the fit is right and hits a button to complete robotic assembly. The Ford co-bot’s ability to fist-bump human coworkers, make coffee, and give scalp massages is just icing on the cake.
In the US, Europe, and Japan, manufacturers embraced robotics to reduce costs and better compete with a host of low-cost entrants — namely China. But as wages in China have risen and its workforce shrinks, it is discovering it faces the same issues its Western counterparts faced decades ago — losing out to foreign competitors with lower labor costs. So Chinese manufacturing is also investing heavily in robotics. China became the world’s largest market for industrial robots in 2013 and last year accounted for 25% of the global market. China’s annual consumption of industrial robots is expected to rise from about 67,000 in 2015 to 150,000 by 2018. The robots China is buying are increasingly collaborative ones that work alongside humans on the assembly line. Such co-bots are smaller, cheaper, and capable of assembling smaller products such as consumer electronics, watches, and apparel.
But while human beings and robots get chummier on the assembly line, collaborative robots are getting smarter. Machine learning algorithms will enable robots to access big data, recognize people, distinguish other machines and parts, make decisions, and act on them. In other words, they’ll be able to do the parts of the “collaboration” with humans that human workers are now doing.
Many worry such collaboration starts to feel less like cooperation and more like training your lower-cost replacement. But robotics experts believe humans won’t be so much replaced as the nature of the human-robot collaboration will evolve. Workers will have to do more nonroutine tasks, and move away from simple problem solving. Computers excel at solving problems, but lack the ability to ask questions about what problems need to be solved. In a world where robots have better skills and knowledge, asking the right questions and identifying what you don’t know will keep the robots where they belong — solving the identified problems and making the coffee.
James Bryant is an industry editor for Dun & Bradstreet. Based in Austin, Texas, he writes about issues affecting the global manufacturing sector. He’s been the company’s specialist on the auto industry for 15 years.