Manufacturers have been using robots and automated applications for a number of years, but new technologies could give machines the ability to think intelligently and learn to optimize their own performance.
Michael May, head of Technology Field Analytics & Monitoring at Siemens Corporate Technology, told an audience of reporters and analysts at the company’s Innovation Lab in Princeton, N.J., recently that artificial intelligence is the next big disruption in manufacturing. He said AI will spark revolutions in both intelligence and autonomy. Whereas some of these things “were considered science fiction just a few years ago,” machines are now showing “human-like” performance in some areas such as object detection, face recognition in images, translation of languages and even artistic capabilities. He said Siemens has been working on “neural network” technologies and behavior prediction capabilities which are modeled on the human brain.
It has the potential not only to make machines more intelligent, but to create “self-optimizing” systems that can continually learn over time to improve their behavior. “So in the past, they collected the data, and then figured out how it could be done differently with a better strategy,” May said.
The technology can offer big benefits for manufacturers. In 2014, Siemens started working on spider worker robots that can know exactly where they are in a particular environment and can find their way back to a charging station, then transmit data to another unit that can pick up the task right where the other robot left off. These robots use onboard cameras and laser scanners to view and interpret their environment.
Siemens is testing the spiders (also known as SiSpis—Siemens Spiders), for a new application of mobile manufacturing where the machines can work collaboratively. Livio Dalloro, head of the product design, modeling and simulation research group in the Automation and Control Technology Field at Siemens Corporate Technology, said the goal has been to create a prototype platform for autonomous manufacturing machines that can understand a task, divide the work among available robots then enter into their own manufacturing process in a coordinated way without the need for explicit programming.
“We are looking at using multiple autonomous robots for collaborative additive manufacturing of structures, such as car bodies, the hulls of ships and airplane fuselages,” Dalloro said.
Researchers said the next step is to transfer the accumulated knowledge of software and algorithms from the spider bots to larger industrial robots that can enable collaborative and mobile manufacturing on a larger level.
While AI-powered robots bring great promise for manufacturers, they also bring fear for some workers. A PwC study found that more than a third of U.S. jobs could be a “high risk” for automation by the early 2030s due to the anticipated capabilities of robotics and artificial intelligence. This is expected to happen not just in manufacturing, but in other sectors like finance and transportation.
Yet many economic, legal and regulatory challenges remain before there can be widespread adoption of such robots. The cost with maintenance and repairs will still likely be higher than that of human workers for quite a while. Regulatory and legal issues also could add years of delays to any sort of mass application.
Treasury Secretary Steven Mnuchin said he is not concerned, as automation has mainly been taking low-paying jobs and is enabling human workers to do more productive jobs at higher wages. “I think we’re so far away from that that it’s not even on my radar screen. I think it’s 50 or 100 more years. We need to make sure we are investing in education and training for the American worker,” Mnuchin said.