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A Hybrid Approach to Implement Data Driven Optimization into Production Environments

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Business Information Systems (BIS 2018)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 320))

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Abstract

The potential of data analytics to improve business processes is commonly recognized. Despite the general enthusiasm, the implementation of data-driven methods in production environments remains low. Although established models, such as CRISP-DM, offer a structured process in order to deploy data analytics in the industry, manufacturing companies still need to choose a starting point, assess the business benefit, and determine a pragmatic course of action. In this paper, we introduce an approach to handle these issues based on a case study from automotive manufacturing. The results are discussed based on a set of requirements derived from the case study.

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Author information

Authors and Affiliations

  1. Institute of Parallel and Distributed Systems, University of Stuttgart, Universitätsstr. 38, 70569, Stuttgart, Germany

    Rachaa Ghabri, Pascal Hirmer & Bernhard Mitschang

Authors
  1. Rachaa Ghabri
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  2. Pascal Hirmer
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  3. Bernhard Mitschang
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Corresponding author

Correspondence to Rachaa Ghabri .

Editor information

Editors and Affiliations

  1. Poznan University of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. Fraunhofer FOKUS, Berlin, Germany

    Adrian Paschke

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Ghabri, R., Hirmer, P., Mitschang, B. (2018). A Hybrid Approach to Implement Data Driven Optimization into Production Environments. In: Abramowicz, W., Paschke, A. (eds) Business Information Systems. BIS 2018. Lecture Notes in Business Information Processing, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-319-93931-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-93931-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93930-8

  • Online ISBN: 978-3-319-93931-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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