Making Sense of Manufacturing Data

Jon Kepa Gerrikagoitia, Gorka Unamuno, Anne Sanz

2016

Abstract

A fast and successful digitation of the industry is meant to be a key issue for Europe in order to maintain its leading role. The new industrial revolution will be based on data as raw material, where the digital economy will merge as a real economy. The challenges for a “hard” sector where traditionally the “soft” has not been considered as an asset are evident and notorious. In this paper IK4-IDEKO, as part of a machine tool builder group, DANOBATGROUP, provides a vision of the challenge and the approach for the solution, supported by results of the current work.

References

  1. Erol, S. (2016). Strategic guidance towards Industry 4.0, a three-stage process model.
  2. Briefing Industry 4.0. Digitalisation for productivity and growth. (2015). ch-en-manufacturing-industry-4-0- 24102014. (n.d.).
  3. Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey, 171-209. http://doi.org/10.1007/s11036-013-0489-0.
  4. Lee, J., Kao, H. A., & Yang, S. (2014). Service innovation and smart analytics for Industry 4.0 and big data environment. Procedia CIRP, 16, 3-8. http://doi.org/10.1016/j.procir.2014.02.001.
  5. F., Chen P., Deng J., Wan, D., Zhang, A. V., Vasilakos X., Rong. (2015). Data mining for the internet of things: Literature review and challenges. International Journal of Distributed Sensor Networks, 2015(i). http://doi.org/10.1155/2015/431047.
  6. Vandermerwe, S., & Rada, J. (1989). Servitization of business: adding value by adding services. European Management Journal, 6(4), 314-324.
  7. Baines, T. S., Lightfoot, H. W., Benedettini, O., & Kay, J. M. (2009). The servitization of manufacturing: a review of literature and reflection on future challenges. Journal of Manufacturing Technology Management, 20(5), 547-567.
  8. Martinez, V., Bastl, M., Kingston, J., & Evans, S. (2010). Challenges in transforming manufacturing organisations into product-service providers. Journal of Manufacturing Technology Management, 21(4), 449-469.
  9. Mont, O. (2004). Product-service systems: panacea or myth?. Lund University.
  10. Davenport, T. H., & Patil, D. J. (2012). Data Scientist. Harvard Business Review, (October), 70-76.
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Paper Citation


in Harvard Style

Gerrikagoitia J., Unamuno G. and Sanz A. (2016). Making Sense of Manufacturing Data . In Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-198-4, pages 590-594. DOI: 10.5220/0005999005900594


in Bibtex Style

@conference{icinco16,
author={Jon Kepa Gerrikagoitia and Gorka Unamuno and Anne Sanz},
title={Making Sense of Manufacturing Data},
booktitle={Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2016},
pages={590-594},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005999005900594},
isbn={978-989-758-198-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Making Sense of Manufacturing Data
SN - 978-989-758-198-4
AU - Gerrikagoitia J.
AU - Unamuno G.
AU - Sanz A.
PY - 2016
SP - 590
EP - 594
DO - 10.5220/0005999005900594