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Process Discovery Method in Dynamic Manufacturing and Logistics Environments

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Book cover Subject-Oriented Business Process Management. The Digital Workplace – Nucleus of Transformation (S-BPM ONE 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1278))

Abstract

Process mining is a promising way to extract insight knowledge on business processes in manufacturing and logistics. However, implementing process mining is challenging in dynamic and complex environments as the discovered process models may not reach the aspired quality. As a result, current process mining solutions do not hold in practical situations effectively in the domain of manufacturing and logistics. In this paper, we propose a sequence clustering methodology based on Markov Chains and Expectation-Maximization. We propose two approaches to improve the existing method of sequence clustering which provide improvement of finding the main behavior and its variants for each process cluster. We evaluate the proposed methodology with real-world data sets by measuring model quality dimensions. The results demonstrate that the proposed methodology is capable to improve process discovery when confronted with dynamic and complex business processes. The resulting models present the main behavior of business processes miming and process variants with a satisfying process model quality.

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Author information

Authors and Affiliations

  1. International Graduate School for Dynamics in Logistics, University of Bremen, Bremen, Germany

    Wacharawan Intayoad & Otthein Herzog

  2. Faculty of Business Studies, University of Applied Science Emden/Leer, Emden, Germany

    Till Becker

  3. Department of Mathematics/Informatics, University of Bremen, Bremen, Germany

    Wacharawan Intayoad & Otthein Herzog

Authors
  1. Wacharawan Intayoad
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  2. Till Becker
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  3. Otthein Herzog
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Corresponding author

Correspondence to Wacharawan Intayoad .

Editor information

Editors and Affiliations

  1. University of Bremen and Bremer Institut für Produktion und Logistik GmbH, Bremen, Germany

    Michael Freitag

  2. Universität Bremen, Bremen, Germany

    Aseem Kinra

  3. Universität Bremen, Bremen, Germany

    Herbert Kotzab

  4. Universität Bremen, Bremen, Germany

    Hans-Jörg Kreowski

  5. University of Bremen and Bremer Institut für Produktion und Logistik GmbH, Bremen, Germany

    Klaus-Dieter Thoben

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Intayoad, W., Becker, T., Herzog, O. (2020). Process Discovery Method in Dynamic Manufacturing and Logistics Environments. In: Freitag, M., Kinra, A., Kotzab, H., Kreowski, HJ., Thoben, KD. (eds) Subject-Oriented Business Process Management. The Digital Workplace – Nucleus of Transformation. S-BPM ONE 2020. Communications in Computer and Information Science, vol 1278. Springer, Cham. https://doi.org/10.1007/978-3-030-64351-5_10

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  • DOI: https://doi.org/10.1007/978-3-030-64351-5_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64350-8

  • Online ISBN: 978-3-030-64351-5

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