Article in Proceedings INPROC-2016-07

BibliographyGröger, Christoph; Kassner, Laura; Hoos, Eva; Königsberger, Jan; Kiefer, Cornelia; Silcher, Stefan; Mitschang, Bernhard: The Data-Driven Factory. Leveraging Big Industrial Data for Agile, Learning and Human-Centric Manufacturing.
In: Hammoudi, Slimane (ed.); Maciaszek, Leszek (ed.); Missikoff, Michele M. (ed.); Camp, Olivier (ed.); Cordeiro, Jose (ed.): Proceedings of the 18th International Conference on Enterprise Information Systems.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 40-52, english.
SciTePress, April 25, 2016.
ISBN: 978-989-758-187-8.
Article in Proceedings (Conference Paper).
CR-SchemaH.4.0 (Information Systems Applications General)
J.2 (Physical Sciences and Engineering)
KeywordsIT Architecture, Data Analytics, Big Data, Smart Manufacturing, Industrie 4.0

Global competition in the manufacturing industry is characterized by ever shorter product life cycles, increas-ing 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 manu-facturing 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 architecture and discuss its conceptual components with respect to service-oriented integration, ad-vanced 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 sce-nario from the automotive industry to demonstrate the benefits of the data-driven factory.

CopyrightScitepress 2016. The paper is presented and published at ICEIS 2016 ( in April 2016. The final publication is available at
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Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
Entry dateApril 7, 2016
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