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.

References

  1. Berners-Lee, T., Hendler, J., Lassila, O., 2001, The Semantic Web, Scientific American, 284(5):34-43.
  2. Zillner, S., et al., 2014, A Semantic Modeling Approach for the Steel Production Domain, 1th European Steel Technology & Application Days & 31th Journées Sidérurgiques Internationales (JSI), Paris.
  3. Chondrogiannis, E., Matskanis, N., et al., 2011, Enabling semantic interlinking of medical data sources and EHRs for clinical research purposes, eChallenges conference.
  4. Haag, S., Cummings, M., 2006, Management Information Systems for the Information Age, pp. 224-228.
  5. Uddin, M. K., et al., 2011, An ontology-based semantic foundation for flexible manufacturing systems, 37th Annual Conference of the IEEE Industrial Electronics Society, IECON 2011, pp. 340-345.
  6. Yang, Z., et al, 2005, Automating integration of manufacturing systems and services: a semantic Web services approach, 31st Annual Conference of IEEE Industrial Electronics Society, IECON 2005.
  7. Martin, L., Tsiknakis, M., et al. 2008, Ontology based integration of distributed and heterogeneous data sources in ACGT, 1st International Conference on Health Informatics, HEALTHINF 2008, (vol. 1, pp. 301-306).
  8. Bizer, C., Seaborne, A. 2004, D2RQ - Treating Non-RDF Databases as Virtual RDF Graphs, International Semantic Web Conference (ISWC2004).
  9. Hardi, J., 2014, Introduction to Semantika DRM, http://www.codeproject.com/Articles/787371/Introduc tion-to-Semantika-DRM.
  10. Vrandecic, D., Krötzsch, M., 2009, Semantic MediaWiki. In John D. et al., eds.: Semantic Knowledge Management. Springer.
  11. Heath, T. Bizer C., Berners-Lee, T., 2010. Linked data-the story so far, International Journal on Semantic Web and Information Systems, Vol. 5(3), Pages 1-22. DOI: 10.4018/jswis.2009081901
  12. Sadalage, P., Fowler, M., 2012, NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence, Addison-Wesley, ISBN 0-321-82662-0.
Download


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