Machine Learning in der adaptiven Fertigungssteuerung

Genetischer Algorithmus zur Bewertung alternativer Arbeitspläne

authored by: Berend Denkena, Sören Wilmsmeier, Florian Winter
Abstract: In work planning, static conditions are currently assumed and supposedly optimal production sequences are defined before start of production. Dynamic influences during production lead to unsystematic rescheduling and an inefficient planning result. Therefore, a machine learning approach for adaptive production control using genetic algorithms is presented.
Organisation(s): Institute of Production Engineering and Machine Tools
External Organisation(s): Fauser AG
Type: Article
Journal: Fabriksoftware
Volume: 24
Pages: 17-20
No. of pages: 4
ISSN: 2569-7692
Publication date: 2019
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Management of Technology and Innovation, Software, Computer Science Applications, Information Systems, Information Systems and Management, Industrial and Manufacturing Engineering
Sustainable Development Goals: SDG 9 - Industry, Innovation, and Infrastructure
Electronic version(s): https://www.fabriksoftware.info/node/1048 (Access: Open)
https://factory-innovation.de/themen/technologien/artikel/machine-learning-in-der-adaptiven-fertigungssteuerung/ (Access: Open)