Nov. 13, 2018 – Fraunhofer FOKUS, Berlin, Germany

Peter Seeberg

Softing Industrial Automation GmbH, Germany

Peter Seeberg studied Computer Aided Design in Delft. After a career in the IT industry (Intel, Infor, Seiko, Mentor), seven years ago he came to Softing and since then has been working towards the integration of IT and industrial automation. Peter has been actively involved in the introduction of Industry 4.0 at Bitkom, VDMA, OPC Foundation and Smart Factory. He is an active member of the Europe Advisory Council of the OPC Foundation and the Machine Learning Expert Group at VDMA. Three years ago he co-founded the internal start-up Industrial Data Intelligence which has meanwhile been transferred to the new business unit Data Intelligence, which deals with the implementation of digital data exchange between production and IT in industrial applications.

Machine Learning based Industrial Edge Analytics for Real-time On-Site Insight


Data and the resulting sequence change from “algorithm -> data -> decision” towards “data -> algorithm -> decision“ drive a revolutionary change.

Algorithms can help improve Overall Equipment Effectiveness, representing machine availability and performance as well as the quality of produced goods.

The goal – improving OEE – is not new. New is the data-based approach by means of machine learning algorithms.

An “edge“ solution close to or part of field devices and machines addresses the decision maker’s unwillingness moving production data into the cloud, and allows data to stay in the production line and to be processed on the spot.

The steps taken from initial workshop through proof of concept, concept development, project execution and deployment, as well as tasks on client and solution provider side, including milestones and eventual results brought forward by the live scoring system will be shared in the presentation.