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Transitioning to Semantic Information<br />

“We simply tell the robot to<br />

attach a specific component to<br />

the mounting rail,” says Wurm.<br />

“And that’s exactly what it<br />

does.” On a small scale, this<br />

task describes what batch size 1<br />

is all about. It involves<br />

manufacturing or assembling a<br />

product in a wide variety of<br />

variants that contain different<br />

components. The robot gets<br />

the information on how to<br />

manufacture a product from an<br />

associated software model.<br />

Although this CAD/CAM<br />

(Computer Aided Design and<br />

Manufacturing) model is<br />

incomprehensible for<br />

conventional robots, the new<br />

prototype can understand such<br />

models. In a sense, it is as if the<br />

robot can understand different<br />

languages, thus eliminating the<br />

need to program its<br />

movements and processes.<br />

To do this, the prototype<br />

successively divides tasks, such<br />

as the general command<br />

“assemble,” from the software<br />

construction plan into doable<br />

units, such as “pick” and “hand<br />

over” until it finally moves an<br />

arm or opens its grippers. The<br />

robot itself also decides which<br />

task each arm should perform.<br />

To make this possible, the<br />

developers have enabled the<br />

prototype to raise information<br />

from the product development<br />

software to a semantic level.<br />

“Product parts and process<br />

information are semantically<br />

converted into ontologies and<br />

knowledge graphs,” says Wurm.<br />

“This makes implicit information<br />

explicit. Until now the<br />

A great objective: With their research, Georg Wichert (left) and Kai Wurm have demonstrated that<br />

economical batch size 1 production is possible.<br />

things that people simply know from<br />

experience when they are told to snap<br />

component X onto rail Y have had to be<br />

taught to robots in the form of code.<br />

However, our prototype analyzes the<br />

problem by itself and finds a corresponding<br />

solution.”<br />

In the case of Siemens’ prototype<br />

demonstrator, one can witness this<br />

process in a vastly simplified form on a<br />

monitor to the right of the robot arms.<br />

The monitor displays two rows of color<br />

tiles, each of which bears words such as<br />

“assemble” (left-hand column) and “pick”<br />

(right-hand column). These tiles gradually<br />

move upward in a manner similar to<br />

scrolling down a long webpage. The tiles<br />

depict each assembly step. On the<br />

monitor to the left, the demonstrator<br />

shows the information that the robot<br />

arms receive at the beginning of a<br />

production process. This information<br />

consists of a 3D depiction of the<br />

surrounding area and the objects it<br />

contains. Above the demonstrator are two<br />

more screens that show what the robot<br />

arms are currently seeing through their<br />

integrated cameras.<br />

Toward Self-Correcting Systems<br />

Siemens Corporate Technologies’<br />

prototype system can also<br />

correct faults without having to<br />

be told beforehand that this is<br />

an option. If a part slips, for<br />

example, one of its arms will<br />

find the part as long as it is<br />

within its camera’s field of<br />

vision. The arm will then pick<br />

up the component and adjust<br />

all of its subsequent movements<br />

so that it can still install<br />

it correctly. And if the component<br />

needs to be snapped into<br />

place on the other side of an<br />

assembly, the arm will hand the component<br />

to its counterpart. These groundbreaking<br />

developments are part of the<br />

Company Core Technology (CCT) Future<br />

of Automation program. CCTs enable<br />

Siemens to focus on crucial fields of<br />

innovation such as digital twins, artificial<br />

intelligence, and additive manufacturing.<br />

Naturally, assembling control cabinets is<br />

just the beginning. Siemens developers<br />

envision self-organizing production<br />

facilities that responds to autonomously<br />

changing production requirements,<br />

continuously optimize their operations,<br />

and are populated by robots that assist<br />

one another. Such facilities would be a<br />

revolutionary step – essentially systems<br />

that feed themselves with design data,<br />

corrects faults, and calculates all movements<br />

and actions on their own. “There<br />

are many other researchers who are trying<br />

to solve this problem. But there is nothing<br />

comparable to what we have developed<br />

on the market yet,” says Wurm.<br />

• Sandra Zistl<br />

Taken from Pictures of the Future, the Siemens<br />

Magazine for Research and Innovation<br />

<strong>For</strong> more information,<br />

write to insight.in@siemens.com<br />

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