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2024 | OriginalPaper | Chapter

Using Process Mining as a Tool for Process’ Digital Twin to Perform Strategic Maintenance Decisions

Authors : Cleiton Ferreira dos Santos, Alef Berg de Oliveira, André Luiz Micosky, Eduardo de Freitas Rocha Loures, Eduardo Alves Portela Santos

Published in: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems

Publisher: Springer Nature Switzerland

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Abstract

Process mining (PM) and digital twin (DT) present synergy in the context of Industry 4.0 era, as data-driven approaches are leading the way. With this relation, some design principles of DT are accomplished by applying PM techniques in order to extract knowledge from industrial processes. This knowledge can range from singular metrics of indicators through complex process analyzes (comprehension of paths, deviations, frequency, simulation and among others). In this context, the motivation of the work comes from using factory floor process data in a process’ digital twin environment as inputs in the decision layer to make assertive choices in the industrial and/or maintenance environment considering different scenarios of actions. Therefore, the main goal of this paper aims at integrating those fields of study (i.e., process mining, process’ digital twin and decision-making) in an industrial maintenance area to choose or indicate a strategic maintenance action that best fits the evaluated scenario.

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Title: Using Process Mining as a Tool for Process’ Digital Twin to Perform Strategic Maintenance Decisions
Authors: Cleiton Ferreira dos Santos
Alef Berg de Oliveira
André Luiz Micosky
Eduardo de Freitas Rocha Loures
Eduardo Alves Portela Santos
Publisher: Springer Nature Switzerland
Book: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems
Print ISBN: 978-3-031-38164-5

Electronic ISBN: 978-3-031-38165-2

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-3-031-38165-2_6