Process mining in logistics: The need for rule-based data abstraction

Ruud van Cruchten, Hans Weigand

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Organizations struggle to gain insight in how their business processes are conducted in reality. Process mining enables organizations to extract this knowledge by analyzing business events recorded in their information systems. However, the business events recorded in these systems do not always reflect the same level of abstraction as the desired process model that is used by the business. Current process mining approaches give insufficient attention to this gap. This paper proposes several data preparation methods that apply logistic domain knowledge for process mining the material movements within an organization. In addition, an adapted process mining project methodology is presented that explicitly includes these preparation methods.
Original languageEnglish
Title of host publicationProceedings of the 12th International Conference on Research Challenges in Information Science (RCIS 2018)
Place of PublicationBrussels
PublisherIEEE
Pages1-9
ISBN (Print)9781538665176
DOIs
Publication statusPublished - May 2018
Event13th International Conference on Research Challenges in Information Science - Brussels, Belgium
Duration: 29 May 201831 May 2018

Conference

Conference13th International Conference on Research Challenges in Information Science
Abbreviated titleRCIS 2018
CountryBelgium
CityBrussels
Period29/05/1831/05/18

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Keywords

  • process mining
  • event mapping
  • abstraction levels
  • logistics
  • business rules

Cite this

van Cruchten, R., & Weigand, H. (2018). Process mining in logistics: The need for rule-based data abstraction. In Proceedings of the 12th International Conference on Research Challenges in Information Science (RCIS 2018) (pp. 1-9). Brussels: IEEE. https://doi.org/10.1109/RCIS.2018.8406653