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[D] Process Mining for Logistics Applications

BACHELOR Assignment

Process Mining for Logistics Applications

Type: Bachelor CS, Bachelor BIT

Period: TBD

Student: (Unassigned)

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The emerging discipline Process Mining (PM) is rapidly gaining attention. PM aims to obtain insight into how business processes are executed, facilitating enhanced decision-making in, for example, supply chain processes. "Process mining is a family of techniques in the field of process management that support the analysis of business processes based on event logs" [1]. Typical enterprise information systems and enterprise resource planning systems contain millions of data records about events, which can be analyzed by PM algorithms.


The goal of this assignment is to study the possibilities of process mining in a logistics (IoT-driven) context. Possible directions include:

  1. Exhaustive (systematic) literature review about process mining applications in the logistics domain. Classify or categorize existing research and identify future research directions. Consequently, depending on how exhaustive the review is, one of the addressed future research directions may be the starting point for designing and developing a new technique.
  2. Advance state-of-the-art in process mining algorithms applied to the logistics domain.
  3. Advance state-of-the-art in logistics enterprise resource planning systems or decision-support systems by means of process mining.

Possible Outcome:

  • Basic understanding (or willingness to learn) of process mining
  • Interest in the domain of transport and logistics



[2] R. H. Bemthuis, M. Koot, M. R. K. Mes, F. A. Bukhsh, M. Iacob and N. Meratnia, "An Agent-Based Process Mining Architecture for Emergent Behavior Analysis," 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW), 2019, pp. 54-64.