Self-learning assistance system for efficient processes

June 1, 2018, Fraunhofer-Gesellschaft
SAM, a self-learning assistance system, helps machine operators resolve errors in production machines. Credit: Fraunhofer IVV

To prevent long downtimes and high quantities of scrap, manufacturers must design production processes to be stable and efficient. Particularly successful outcomes are achieved when the experience of the people who operate the machines is taken into account. The Fraunhofer Institute for Process Engineering and Packaging IVV in Dresden is developing a self-learning assistance system that helps machine operators resolve errors and build up their experience and process knowledge.

To take a concrete example: On a processing machine, chocolate bars are wrapped in paper. A sensor detects a deviation in the production process and the machine stops. Even with state-of-the-art systems, a brief interruption occurs on average every five minutes. An experienced machine operator knows where the cause of the error lies. He or she sees that the paper is bending and concludes that, in this case, the speed of the machine needs to be regulated. However, this knowledge is person-specific – a colleague with less experience would need more time to find the solution.

To make this experience-based knowledge available to all operators at all times, scientists at Fraunhofer IVV in Dresden are developing SAM, a self-learning assistance system for machine operators. The system observes machine states and operator actions and saves successful solution strategies. Using a tablet computer, for example, the machine operator inputs his/her solution and then links it to the current fault situation recorded by SAM. If a given fault has occurred several times, SAM recognizes it and can give the operator tips on the cause and on how to solve the problem. In this way, the machine is quickly repaired and running again.

To enable SAM to learn fault situations, the scientists at Fraunhofer IVV are using machine learning algorithms. Equipped with intelligent feature extraction, SAM is able to learn at a similar speed as humans and can recognize patterns after only a few repetitions. "Thanks to our knowledge of packaging machine processes, we're able to make SAM very fast," explains Andre Schult, Group Manager for Digitalization and Process Efficiency at Fraunhofer IVV.

Working with SAM is a people-centered experience

When designing SAM, Fraunhofer IVV in Dresden put people at the center of their considerations. "A human being is a wonderful tool. With their hands and eyes, they are more flexible and better than many robots or cameras," says Andre Schult. However, processes and systems are growing in complexity all the time. With SAM, Schult also wants to enable operators in the future to recognize errors themselves and suggest their own solutions. People should know that, despite all the state-of-the-art technology, humans play an indispensable role in production. This increases their sense of value in their work and their motivation.

Together with partners from industry and science, Fraunhofer IVV plans to further develop the self-learning operator assistance system over the next five years and add new functionalities through a range of new modules. In this way, it will be possible to adapt SAM to specific customer requirements. Possible additional features include things like the use of image processing, external sensors, and speech and gesture recognition. Looking forward, manufacturers will be able to use SAM both for the operation and for the maintenance, setup, assembly and development of .

Explore further: Better quality control with digital assistance systems

Related Stories

Better quality control with digital assistance systems

July 1, 2016

Errors can be spotted early and resources can be saved when many individuals share knowledge in a company. This is the case with a honing machine used to hone crankcases at VW's engine plant in Salzgitter: A digital assistance ...

Produce more flexibly with the Industry Cockpit

April 9, 2015

Customers expect products to be tailored to their needs. And not only that: they want to influence the way the product is manufactured as well. As a result, very flexible manufacturing and administrative processes are necessary. ...

Cognitive sensors in production processes

February 6, 2018

As a direct result of Industrie 4.0, industrial production is becoming increasingly customized. And industry's long-term goal is batch size one. In practice, however, digitalization still frequently means individual solutions ...

New safety technology enables teamwork

March 27, 2017

Until now, heavy-duty robots have always been housed in separate work areas to safeguard factory employee safety. Researchers at Fraunhofer want to change that with an ingenious security concept and intelligent robot control. ...

New machine evaluates soybean at harvest for quality

October 3, 2017

When a field of soybeans is ready to harvest, speed is of the essence. But harvesting grinds to a halt every time the combine operator has to climb down out of the cab to manually check for quality—whole, un-split beans ...

Recommended for you

Apple closing iPhone security gap used by law enforcement

June 14, 2018

Apple is closing a security gap that allowed outsiders to pry personal information from locked iPhones without a password, a change that will thwart law enforcement agencies that have been exploiting the vulnerability to ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.