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Authors: Christoph Gröger 1 ; Laura Kassner 2 ; Eva Hoos 2 ; Jan Königsberger 2 ; Cornelia Kiefer 2 ; Stefan Silcher 3 and Bernhard Mitschang 2

Affiliations: 1 University of Stuttgart and Robert Bosch GmbH, Germany ; 2 University of Stuttgart, Germany ; 3 University of Stuttgart and eXXcellent solutions GmbH, Germany

Keyword(s): IT Architecture, Data Analytics, Big Data, Smart Manufacturing, Industrie 4.0.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Coupling and Integrating Heterogeneous Data Sources ; Data Mining ; Data Warehouses and OLAP ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Global competition in the manufacturing industry is characterized by ever shorter product life cycles, increasing complexity and a turbulent environment. High product quality, continuously improved processes as well as changeable organizational structures constitute central success factors for manufacturing companies. With the rise of the internet of things and Industrie 4.0, the increasing use of cyber-physical systems as well as the digitalization of manufacturing operations lead to massive amounts of heterogeneous industrial data across the product life cycle. In order to leverage these big industrial data for competitive advantages, we present the concept of the data-driven factory. The data-driven factory enables agile, learning and human-centric manufacturing and makes use of a novel IT architecture, the Stuttgart IT Architecture for Manufacturing (SITAM), overcoming the insufficiencies of the traditional information pyramid of manufacturing. We introduce the SITAM arc hitecture and discuss its conceptual components with respect to service-oriented integration, advanced analytics and mobile information provisioning in manufacturing. Moreover, for evaluation purposes, we present a prototypical implementation of the SITAM architecture as well as a real-world application scenario from the automotive industry to demonstrate the benefits of the data-driven factory. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Gröger, C.; Kassner, L.; Hoos, E.; Königsberger, J.; Kiefer, C.; Silcher, S. and Mitschang, B. (2016). The Data-driven Factory - Leveraging Big Industrial Data for Agile, Learning and Human-centric Manufacturing. In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-187-8; ISSN 2184-4992, SciTePress, pages 40-52. DOI: 10.5220/0005831500400052

@conference{iceis16,
author={Christoph Gröger. and Laura Kassner. and Eva Hoos. and Jan Königsberger. and Cornelia Kiefer. and Stefan Silcher. and Bernhard Mitschang.},
title={The Data-driven Factory - Leveraging Big Industrial Data for Agile, Learning and Human-centric Manufacturing},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2016},
pages={40-52},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005831500400052},
isbn={978-989-758-187-8},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - The Data-driven Factory - Leveraging Big Industrial Data for Agile, Learning and Human-centric Manufacturing
SN - 978-989-758-187-8
IS - 2184-4992
AU - Gröger, C.
AU - Kassner, L.
AU - Hoos, E.
AU - Königsberger, J.
AU - Kiefer, C.
AU - Silcher, S.
AU - Mitschang, B.
PY - 2016
SP - 40
EP - 52
DO - 10.5220/0005831500400052
PB - SciTePress