Coping with concept drift in a virtual metrology application to predict part quality in micro gear manufacturing
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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in: Measurement: Sensors, 2025.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Coping with concept drift in a virtual metrology application to predict part quality in micro gear manufacturing
AU - Bilen, Ali
AU - Grommes, Aaron
AU - Stamer, Florian
AU - Lanza, Gisela
N1 - Publisher Copyright: © 2024
PY - 2025
Y1 - 2025
N2 - This study is focused on advancing the application of structure-borne sound sensors in the manufacturing of micro gears. A robust approach is developed through the incorporation of machine learning techniques to address concept drift, especially resulting from tool wear during the hobbing process. A detailed long-term study is undertaken to refine the predictive models, ensuring their accuracy in the face of a dynamic manufacturing environment. By tackling the challenges associated with concept drift, the capabilities of acoustic emission sensing are sought to be fully exploited. The aim is to enhance the reliability and precision of quality predictions, establishing a new benchmark in the field and significantly contributing to the optimization of micro gear production processes.
AB - This study is focused on advancing the application of structure-borne sound sensors in the manufacturing of micro gears. A robust approach is developed through the incorporation of machine learning techniques to address concept drift, especially resulting from tool wear during the hobbing process. A detailed long-term study is undertaken to refine the predictive models, ensuring their accuracy in the face of a dynamic manufacturing environment. By tackling the challenges associated with concept drift, the capabilities of acoustic emission sensing are sought to be fully exploited. The aim is to enhance the reliability and precision of quality predictions, establishing a new benchmark in the field and significantly contributing to the optimization of micro gear production processes.
KW - Acoustic emission
KW - AI
KW - Micro gears
KW - Quality assurance
KW - Quality prediction
KW - Virtual metrology
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85213942278&partnerID=8YFLogxK
U2 - 10.1016/j.measen.2024.101797
DO - 10.1016/j.measen.2024.101797
M3 - Journal articles
AN - SCOPUS:85213942278
JO - Measurement: Sensors
JF - Measurement: Sensors
SN - 2665-9174
M1 - 101797
ER -