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Towards Learning- and Knowledge-Based Methods of Artificial Intelligence for Short-Term Operative Planning Tasks in Production and Logistics

Research Idea and Framework
 
: Lang, S.; Schenk, M.; Reggelin, T.

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IFAC-PapersOnLine 52 (2019), No.13, pp.2716-2721
ISSN: 2405-8963
ISSN: 1474-6670
Conference on Manufacturing, Modelling, Management and Control (IFAC-MIM) <9, 2019, Berlin>
English
Conference Paper, Journal Article
Fraunhofer IFF ()

Abstract
Driven by the increasing digitalization, experts estimate a major change concerning the planning and operation of production systems. The trends indicate a shift from centrally controlled and fixed interlinked production resources to a decentralized production consisting of self-managing cyber-physical systems. This article describe the resulting challenges for the short-term operative production and logistics planning as well as the limitations of current methods. In the further course, the article discusses application potentials of artificial neural networks and fuzzy logic to tackle short-term operative planning tasks in production and logistics. The article concludes with a research framework, which outlines our future steps.

: http://publica.fraunhofer.de/documents/N-585451.html