Making sense of manufacturing data

Jon Kepa Gerrikagoitia; Gorka Unamuno; Anne Sanz

doi:10.5220/0005999005900594

Making sense of manufacturing data

Jon Kepa Gerrikagoitia
, Gorka Unamuno
, Anne Sanz

IDEKO

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

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.

Original language	English
Title of host publication	ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics
Editors	Oleg Gusikhin, Dimitri Peaucelle, Kurosh Madani
Publisher	SciTePress
Pages	590-594
Number of pages	5
ISBN (Electronic)	9789897581984
DOIs	https://doi.org/10.5220/0005999005900594
Publication status	Published - 2016
Externally published	Yes
Event	13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016 - Lisbon, Portugal Duration: 29 Jul 2016 → 31 Jul 2016

Publication series

Name	ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics
Volume	2

Conference

Conference	13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016
Country/Territory	Portugal
City	Lisbon
Period	29/07/16 → 31/07/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Big data analytics
Data science
Digital factory
Industry 4.0
Smart manufacturing

Access to Document

10.5220/0005999005900594

Cite this

Gerrikagoitia, J. K., Unamuno, G., & Sanz, A. (2016). Making sense of manufacturing data. In O. Gusikhin, D. Peaucelle, & K. Madani (Eds.), ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (pp. 590-594). (ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics; Vol. 2). SciTePress. https://doi.org/10.5220/0005999005900594

Gerrikagoitia, Jon Kepa ; Unamuno, Gorka ; Sanz, Anne. / Making sense of manufacturing data. ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics. editor / Oleg Gusikhin ; Dimitri Peaucelle ; Kurosh Madani. SciTePress, 2016. pp. 590-594 (ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics).

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title = "Making sense of manufacturing data",

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.",

keywords = "Big data analytics, Data science, Digital factory, Industry 4.0, Smart manufacturing",

author = "Gerrikagoitia, \{Jon Kepa\} and Gorka Unamuno and Anne Sanz",

note = "Publisher Copyright: Copyright {\textcopyright} 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.; 13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016 ; Conference date: 29-07-2016 Through 31-07-2016",

year = "2016",

doi = "10.5220/0005999005900594",

language = "English",

series = "ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics",

publisher = "SciTePress",

pages = "590--594",

editor = "Oleg Gusikhin and Dimitri Peaucelle and Kurosh Madani",

booktitle = "ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics",

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Gerrikagoitia, JK, Unamuno, G & Sanz, A 2016, Making sense of manufacturing data. in O Gusikhin, D Peaucelle & K Madani (eds), ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics. ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics, vol. 2, SciTePress, pp. 590-594, 13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016, Lisbon, Portugal, 29/07/16. https://doi.org/10.5220/0005999005900594

Making sense of manufacturing data. / Gerrikagoitia, Jon Kepa; Unamuno, Gorka; Sanz, Anne.
ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics. ed. / Oleg Gusikhin; Dimitri Peaucelle; Kurosh Madani. SciTePress, 2016. p. 590-594 (ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Making sense of manufacturing data

AU - Gerrikagoitia, Jon Kepa

AU - Unamuno, Gorka

AU - Sanz, Anne

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Big data analytics

KW - Data science

KW - Digital factory

KW - Industry 4.0

KW - Smart manufacturing

UR - https://www.scopus.com/pages/publications/85013076901

U2 - 10.5220/0005999005900594

DO - 10.5220/0005999005900594

M3 - Conference contribution

AN - SCOPUS:85013076901

T3 - ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics

SP - 590

EP - 594

BT - ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics

A2 - Gusikhin, Oleg

A2 - Peaucelle, Dimitri

A2 - Madani, Kurosh

PB - SciTePress

T2 - 13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016

Y2 - 29 July 2016 through 31 July 2016

ER -

Gerrikagoitia JK, Unamuno G, Sanz A. Making sense of manufacturing data. In Gusikhin O, Peaucelle D, Madani K, editors, ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics. SciTePress. 2016. p. 590-594. (ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics). doi: 10.5220/0005999005900594

Making sense of manufacturing data

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this