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Design of a Data Structure for the Order Processing as a Basis for Data Analytics Methods

  • Today, manufacturing companies are facing the influences of a dynamic environment and the continuously increasing planning complexity. Using advanced data analytics methods, processes can be improved by analyzing historical data, detecting patterns and deriving measures to counteract the issues. The basis of such approaches builds a virtual representation of a product – called the digital twin or digital shadow. Although, applied IT systems provide reliable feedback data of the processes on the shop-floor, they lack on a data structure which represents real-time data series of a product. This paper presents an approach for a data structure for the order processing which overcomes the described issue and provides a virtual representation of a product. Based on the data structure deviations between the production schedule and the real situation on the shop-floor can be identified in real time and measures to reschedule operations can be identified.

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Metadaten
Verfasserangaben:Günther SchuhORCiDGND, Matthias BlumGND
URL:https://ieeexplore.ieee.org/document/7806715
DOI:https://doi.org/10.1109/PICMET.2016.7806715
ISBN:978-1-5090-3595-3
Titel des übergeordneten Werkes (Englisch):2016 Proceedings of PICMET '16: Technology Management for Social Innovation
Herausgeber*in:Dundar F. Kocaoglu
Dokumentart:Konferenzveröffentlichung
Sprache:Englisch
Datum der Veröffentlichung (online):26.07.2023
Datum der Erstveröffentlichung:01.10.2016
Datum der Freischaltung:05.09.2023
Freies Schlagwort / Tag:Digitaler Schatten
GND-Schlagwort:Big DataGND; Industrie 4.0GND
Erste Seite:2164
Letzte Seite:2169
FIR-Nummer:SV6747
Konferenzname:Picmet ’16 Portland International Conference on Management of Engineering and Technology
Konferenzort:Honolulu (HI)
Konferenzzeitraum:04.09.2016-08.09.2016
Institut / Bereiche des FIR:FIR e. V. an der RWTH Aachen
Produktionsmanagement
DDC-Klassifikation:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften