Stefan Eberhardt

Business Development Manager

Kontron S&T

Artificial intelligence (AI) based visual inspection in Automation Industry

This speech gives insight into AI in the automation industry environment.  For this lecture the very broad term of AI is explained and focused on deep leaning, so basically the technology that simulates neurons in order to solve problems.

Start by “what is Deep leaning” in its core, what can be expected from it and what kind of problems can be solved with it the topic gets expained. After that we explain what is needed to put this technology in place and what makes sense. This is accompanied by a live demo that shows and illustrates these elements.

After having explained the foundations we start looking at what can be done with this technology out of a business case perspective. Here we need to look at some border conditions: Depending upon the geographical location there are certain implications like the size of the customer and existing environment or installations, so for example there is a huge difference between Asia and Europe.

Out of this several use cases derive. Focusing on Europe there are basically two main use cases one is basically the retail use case focusing on high volume of devices and/ or a generic approach. While the other one is pre project driven and more focusing on quality control though this topic is not really new in Europe.

Before Stefan Eberhardt started to work as Business Development Manager at Kontron Technologies, he was working for Giesecke & Devrient as Product Manager for IoT and IT-Security, where he specified and developed IoT solutions for the mass market.

He also gained „Hardware aligned Software expertiser“ as Software Product Manager during his time at Kontron as well as in the Building Automatisation area where he lead for more than 5 years the software development at Aumüller GmbH.

Prior to this, Stefan was employed at Oracle Germany in the Server Technologies Competence Center and Fujitsu Siemens Computers where he obtained additional experience in the computing & engineering field.