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Process mining and industrial applications: A systematic literature review
Author(s) -
Corallo Angelo,
Lazoi Mariangela,
Striani Fabrizio
Publication year - 2020
Publication title -
knowledge and process management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.341
H-Index - 44
eISSN - 1099-1441
pISSN - 1092-4604
DOI - 10.1002/kpm.1630
Subject(s) - process mining , computer science , process (computing) , grasp , context (archaeology) , systematic review , data science , data mining , risk analysis (engineering) , process management , work in process , business process , business process management , engineering , software engineering , operations management , business , medline , paleontology , law , political science , biology , operating system
Currently, the process mining aims at an automatic extraction of process knowledge from the event logs recorded by information systems, and, therefore, by using these techniques, it becomes possible to grasp the complex nature of industrial processes. In fact, most of the industrial processes change over time, and through the process mining techniques, it is possible to analyse these processes as if they were in a steady state. Starting to this concept, in this paper, we provide a systematic literature review that analyses the applications of process mining techniques in relation to the industrial context in order to highlight the importance of these new techniques in this scenario. To do the systematic literature review, we use the Tranfield approach (2003), and we identify the most interesting papers in the sector under analysis. After that, an in‐depth analysis of the selected papers was carried out.