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Data analysis and visualization framework in the manufacturing decision support system of COMPOSITION project

 
: Vafeiadis, T.; Kalatzis, D.; Nizamis, A.; Ioannidis, D.; Apostolou, K.; Metaxa, I.N.; Charisi, V.; Beecks, C.; Insolvibile, G.; Pardi, M.; Vergori, P.; Tzovaras, D.

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Fulltext ()

Procedia manufacturing 28 (2019), pp.57-62
ISSN: 2351-9789
International Conference on Changeable, Agile, Reconfigurable and Virtual Production (CARV) <7, 2018, Nantes>
English
Journal Article, Conference Paper, Electronic Publication
Fraunhofer FIT ()

Abstract
The EU Factory of the Future (FoF) project COMPOSITION (Ecosystem for COllaborative Manufacturing PrOceSses – Intra- and Interfactory Integration and AutomaTION) aims to develop an Integrated Information Management System (IIMS) in order to combine physical world, simulation, planning and forecasting data for enhancing re-configurability, scalability and optimisation of resources and processes inside a factory. In addition, the second aim of this project is to extend locally integrated information management systems into an ecosystem that supports the interchange of data and services between factories and their suppliers, i.e., by incorporating and inter-linking both supply and value chains. In this paper, we present an overview of the COMPOSITION project with a particular focus on the incorporation of data analytics tools with the Manufacturing Decision Support System (MDSS) so as to enhance its functionalities. Furthermore, the connection of data analytics tools with a smart Building Management System (BMS) and Digital Factory Modelling (DFM) techniques for data propagation are presented as well. We show how state-of-the-art techniques and methodologies from the research fields of big data analytics, deep learning and simulation/forecasting are incorporated into the MDSS, and how the system is designed in order to accommodate the data-driven needs of a manufacturing environment.

: http://publica.fraunhofer.de/documents/N-630031.html