Integration of domain expert-centric ontology design into the CRISP-DM for cyber-physical production systems
Publication date
2023-10-12
Document type
Konferenzbeitrag
Organisational unit
Conference
28th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2023) ; Sinaia, Romania ; September 12-15, 2023
Project
Publisher
IEEE
Book title
2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
Part of the university bibliography
✅
Language
English
Keyword
dtec.bw
Abstract
In the age of Industry 4.0 and Cyber-Physical Production Systems (CPPSs) vast amounts of potentially valuable data are being generated. Methods from Machine Learning (ML) and Data Mining (DM) have proven to be promising in extracting complex and hidden patterns from the data collected. The knowledge obtained can in turn be used to improve tasks like diagnostics or maintenance planning. However, such data-driven projects, usually performed with the Cross-Industry Standard Process for Data Mining (CRISP-DM), often fail due to the disproportionate amount of time needed for understanding and preparing the data. The application of domain-specific ontologies has demonstrated its advantageousness in a wide variety of Industry 4.0 application scenarios regarding the aforementioned challenges. However, workflows and artifacts from ontology design for CPPSs have not yet been systematically integrated into the CRISP-DM. Accordingly, this contribution intends to present an integrated approach so that data scientists are able to more quickly and reliably gain insights into the CPPS. The result is exemplarily applied to an anomaly detection use case.
Version
Published version
Access right on openHSU
Metadata only access