Journal
IFAC PAPERSONLINE
Volume 51, Issue 11, Pages 316-321Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ifacol.2018.08.302
Keywords
data mining; knowledgebase; association rule learning; production scheduling; productive resources
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The paper proposes an approach to the early detection of factors implying the need in production schedule update. Resource state prediction methods are based on the development of a binary model and a machine learning techniques called association rules search. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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