Learning Systems for Manufacturing Management Support

Heimo Gursch, Andreas Wuttei , Sophie Gangloff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Highly optimised assembly lines are commonly used in various manufacturing domains, such as electronics, microchips, vehicles, electric appliances, etc. In the last decades manufacturers have installed software systems to control and optimise their shop floor processes. Machine Learning can enhance those systems by providing new insights derived from the previously captured data. This paper provides an overview of Machine Learning fields and an introduction to manufacturing management systems. These are followed by a discussion of research projects in the field of applying Machine Learning solutions for condition monitoring, process control, scheduling, and predictive maintenance. Copyright © 2016 for this paper by its authors.
Original languageGerman
Title of host publication1st International Workshop on Science, Application and Methods in Industry 4.0
Publication statusPublished - 2016
Event1st International Workshop on Science, Application and Methods in Industry 4.0 - co-located with the International Conference on Knowledge Technologies and Data-driven Business: SAMI 2016 - iKNOW 2016 - Graz, Austria
Duration: 19 Oct 2016 → …

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS
Volume1793
ISSN (Electronic)1613-0073

Conference

Conference1st International Workshop on Science, Application and Methods in Industry 4.0 - co-located with the International Conference on Knowledge Technologies and Data-driven Business
CountryAustria
CityGraz
Period19/10/16 → …

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