Using Semantic Technologies for More Intelligent Steel Manufacturing

Nikolaos Matskanis, Stephane Mouton, Alexander Ebel, Francesca Marchiori

2015

Abstract

In recent years, the steel industry has significantly raised its demands regarding product quality, optimization of production cost, environmental issues and lead-time. The demand for improved production performance has in turn increased the demand on information systems, in particular highlighting the need for improved factory- and company-wide collaboration and information exchange. The heterogeneity in structure, technology and architecture of the information systems deployed in manufacturing plants presents further challenges to the design and implementation of a data exchange system for process optimization.

Paper Citation

in Harvard Style

Matskanis N., Mouton S., Ebel A. and Marchiori F. (2015). Using Semantic Technologies for More Intelligent Steel Manufacturing . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KEOD, (IC3K 2015) ISBN 978-989-758-158-8, pages 424-428. DOI: 10.5220/0005639004240428

in Bibtex Style

@conference{keod15,
author={Nikolaos Matskanis and Stephane Mouton and Alexander Ebel and Francesca Marchiori},
title={Using Semantic Technologies for More Intelligent Steel Manufacturing},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KEOD, (IC3K 2015)},
year={2015},
pages={424-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005639004240428},
isbn={978-989-758-158-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KEOD, (IC3K 2015)
TI - Using Semantic Technologies for More Intelligent Steel Manufacturing
SN - 978-989-758-158-8
AU - Matskanis N.
AU - Mouton S.
AU - Ebel A.
AU - Marchiori F.
PY - 2015
SP - 424
EP - 428
DO - 10.5220/0005639004240428