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Data-Assisted Value Stream Method

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Production at the leading edge of technology (WGP 2020)

Part of the book series: Lecture Notes in Production Engineering ((LNPE))

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Abstract

The value stream method is widely used in the manufacturing industry to analyze and redesign value streams. However, with the increasing complexity of modern production systems, conducting a value stream analysis (VSA) and extracting reliable information for an accurate value stream design (VSD) becomes a challenging task for practitioners. Utilizing data from production-related IT systems offers the potential to support the value stream method with target-oriented analyses. Process mining (PM) supports the VSA by deriving process flows from production data as well as by analyzing process performances. Focused analyses of master data and transactional data enable reliable VSD activities without having to assume an oversimplified current state. This paper provides a framework for a continuously integrated data assistance within the value stream method, presenting a team structure, best practice procedures, and requirements for the application of the data assisted value stream method supported by examples from industry projects.

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Author information

Authors and Affiliations

  1. Institute for Production Management, Technology and Machine Tools, Technical University of Darmstadt, Otto-Berndt-Str. 2, 64287, Darmstadt, Germany

    C. Urnauer, V. Gräff & J. Metternich

  2. Technical University of Darmstadt, Software & Digital Business Group, Hochschulstr. 1, 64289, Darmstadt, Germany

    C. Tauchert

Authors
  1. C. Urnauer
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  2. V. Gräff
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  3. C. Tauchert
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  4. J. Metternich
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Corresponding author

Correspondence to C. Urnauer .

Editor information

Editors and Affiliations

  1. Institute of Forming Technology and Machines, Garbsen, Germany

    Bernd-Arno Behrens

  2. Institute of Manufacturing Science and Engineering, Dresden, Germany

    Alexander Brosius

  3. Institute of Production Management and Technology, Hamburg, Germany

    Wolfgang Hintze

  4. Institute of Mechatronic Engineering, Dresden, Germany

    Steffen Ihlenfeldt

  5. Laboratorium for Manufacturing Technology, Hamburg, Germany

    Jens Peter Wulfsberg

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Urnauer, C., Gräff, V., Tauchert, C., Metternich, J. (2021). Data-Assisted Value Stream Method. In: Behrens, BA., Brosius, A., Hintze, W., Ihlenfeldt, S., Wulfsberg, J.P. (eds) Production at the leading edge of technology. WGP 2020. Lecture Notes in Production Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62138-7_66

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  • DOI: https://doi.org/10.1007/978-3-662-62138-7_66

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-62137-0

  • Online ISBN: 978-3-662-62138-7

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