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International Conference on Business Process Management

BPM 2019: Business Process Management Workshops pp 56–67Cite as

Supporting Complaint Management in the Medical Technology Industry by Means of Deep Learning

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 362))

Abstract

Complaints about finished products are a major challenge for companies. Particularly for manufacturers of medical technology, where product quality is directly related to public health, defective products can have a significant impact. As part of the increasing digitalization of manufacturing companies (“Industry 4.0”), more process-related data is collected and stored. In this paper, we show how this data can be used to support the complaint management process in the medical technology industry. Working together with a large manufacturer of medical products, we obtained a large dataset containing textual descriptions and assigned error sources for past complaints. We use this dataset to design, implement, and evaluate a novel approach for automatically suggesting a likely error source for future complaints based on the customer-provided textual description. Our results show that deep learning technology holds an interesting potential for supporting complaint management processes, which can be leveraged in practice.

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Notes

  1. 1.

    https://github.com/phakeai/aicomplaint.

  2. 2.

    https://www.tensorflow.org.

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Acknowledgement

This work was conducted within a project sponsored by the German Ministry for Education and Research (BMBF), project name “Reklamation 4.0”, support code “01IS17088B”. We also gratefully acknowledge the support of NVIDIA for the donation of a GPU used for this research.

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Authors and Affiliations

  1. Institute for Information Systems (IWi) at the German Research Center for Artificial Intelligence (DFKI GmbH) and Saarland University, Campus D3.2, Saarbrücken, Germany

    Philip Hake, Jana-Rebecca Rehse & Peter Fettke

Authors
  1. Philip Hake
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  2. Jana-Rebecca Rehse
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  3. Peter Fettke
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Corresponding author

Correspondence to Philip Hake .

Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler, Trento, Italy

    Chiara Di Francescomarino

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Remco Dijkman

  3. University of Vienna, Vienna, Austria

    Uwe Zdun

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Hake, P., Rehse, JR., Fettke, P. (2019). Supporting Complaint Management in the Medical Technology Industry by Means of Deep Learning. In: Di Francescomarino, C., Dijkman, R., Zdun, U. (eds) Business Process Management Workshops. BPM 2019. Lecture Notes in Business Information Processing, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-030-37453-2_6

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  • DOI: https://doi.org/10.1007/978-3-030-37453-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37452-5

  • Online ISBN: 978-3-030-37453-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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