How much autonomy does production tolerate? What are the opportunities and limits of artificial intelligence? A prominent survey with AI professionals from ABB, Siemens, Omron, Schaeffler, DFKI and the robotics startup VisCheck.
What can artificial intelligence do in the production of the future? Where does it make sense and where doesn’t it? If you believe the big buzzword hype around terms like Industry 4.0, the fate of Germany's factories is sealed: Artificial intelligence will take over and pull the strings. Production will become autonomous . And this means that sooner or later, everything will be self-controlling. Or maybe not?
For the correct answer to this question, we first need a closer understanding of the terms: And it's not that easy for artificial intelligence, because there is no clear definition of it. Simply explained, artificial intelligence means
What autonomous production means can be deduced a bit from this. In fact, autonomous production goes far beyond highly automated processes and means production that controls itself, flexibly regulates and optimizes itself and is able to make decisions independently.
Consequently, if production is autonomous, it is strongly AI-driven. However: Completely or to what degree?
“Up to now, AI has only been used very selectively at the tool level in Germany,” Christoph Hildebrandt said, head of image processing and non-destructive testing technology in special-purpose machine manufacturing at Schaeffler. As a tool for what? Axel Lorenz, Head of Automation Systems at Siemens Digital Industries, specified: “For example, artificial intelligence is used today to create transparency and to make suggestions for humans to act. In the future, however, we will see a major step toward independent decisions in the development of AI applications in manufacturing. The degree of autonomy depends on the area of application. For example, this is different in the protection room, in tedious tasks that can result in errors, than in the use of AI for the faster development and scaling of innovative business ideas.”
And of course, the cost-effectiveness of autonomous systems is the decisive criterion in production for their implementation and use. Tim Foreman, European R&D Director at Omron Europe, sees enormous potential in intelligent process optimization and control: “Ideally, AI helps the user to identify and understand cause-effect relationships of undesirable deviations that negatively affect product quality. At the same time, AI can anticipate effects on product quality and even react in real time if necessary.” For this purpose, artificial intelligence can record very large amounts of data and process them into information. For Foreman, such optimization also has an impact on the qualification of employees. This is when sensors and automated visual tools help to improve quality at every step of the production process and thus train employees on the fly.
Incidentally, artificial intelligence is also economical when it comes to building bridges between technology islands, as Guido Bruch from robotics start-up VisCheck explains: “For example, between an old machine that has to be operated individually and a robot that could operate a machine mechanically but is ultimately 'stupid'.”
To get a better idea of what AI-powered autonomous production could look like in the future, a look at the next stage in 2030 is helpful. Scenarios provided by:
In the end, the application sets the tone. AI has to pay off. There will be no autonomous production for its own sake. But if AI pays off, it will more than ever shape the image of production of the future.