Configuration of manufacturing networks by a multi-objective perspective enabled by simulation and machine learning

Elias Franziskus Detlef Auberger*, Hugo Daniel Karre, Matthias Wolf, Heimo Preising, Christian Ramsauer

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Manufacturing companies are facing an increasingly volatile environment today. Internal manufacturing networks are becoming ever more important for ensuring competitive survival. The objective of this research is to introduce an iterative approach for the configuration of manufacturing networks by increasing the transparency for decision making including effects on tactical and operational level. In this context a combined method with discrete event simulation and machine learning is considered. The results of the new approach were validated within a use case at an Austrian company in the railway sector by reconfiguration of the manufacturing network consisting of 4 sites.
Original languageEnglish
Pages (from-to)993-998
Number of pages6
JournalProcedia CIRP
Volume104
DOIs
Publication statusPublished - 26 Nov 2021
Event54th CIRP Conference on Manufacturing Systems: Towards Digitalized Manufacturing 4.0 - Virtuell
Duration: 22 Sep 202124 Sep 2021

Fingerprint

Dive into the research topics of 'Configuration of manufacturing networks by a multi-objective perspective enabled by simulation and machine learning'. Together they form a unique fingerprint.

Cite this