Details
Originalsprache | Englisch |
---|---|
Seiten (von - bis) | 311-316 |
Seitenumfang | 6 |
Fachzeitschrift | International Journal of Advanced Manufacturing Technology |
Jahrgang | 95 |
Ausgabenummer | 1-4 |
Frühes Online-Datum | 20 Okt. 2017 |
Publikationsstatus | Veröffentlicht - März 2018 |
Abstract
The combination of different materials in one workpiece in order to optimize the workpiece characteristics is a state of the art design method for high-performance components. These workpieces can be made of the most qualified materials according to local requirements. However, during machining of material compounds, the different materials have to be considered. This is due to the specific material properties, cutting characteristics, and chip formation mechanisms. Cutting parameters have to be adapted for each material in order to achieve the demanded workpiece quality and optimal processes in respect of tool life and material removal rate. The focus of this research is the development of an in-process material identification algorithm. Thus, a cylindrical turning process is investigated for friction welded aluminum/steel shafts (EN-AW6082/20MnCr5). A universal monitoring approach is presented which detects the different materials process-parallel. For this purpose, cutting forces and spindle torque are linked with a dexel-based material removal model to determine monitoring parameters. The design of experiment method is used to validate the approach for various process parameters. Cutting speed and feed velocity are adapted for cylindrical turning operations based on the monitoring algorithm. As a result, material-specific cutting parameters are adjusted during the machining in order to optimize the material removal rate. Based on this approach, further process optimization can be implemented, like the improvement of chip formation, while machining hybrid workpieces.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Software
- Ingenieurwesen (insg.)
- Maschinenbau
- Informatik (insg.)
- Angewandte Informatik
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
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in: International Journal of Advanced Manufacturing Technology, Jahrgang 95, Nr. 1-4, 03.2018, S. 311-316.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Automatic process parameter adaption for a hybrid workpiece during cylindrical operations
AU - Denkena, Berend
AU - Bergmann, Benjamin
AU - Witt, Matthias
N1 - (c) Springer-Verlag London Ltd. 2017
PY - 2018/3
Y1 - 2018/3
N2 - The combination of different materials in one workpiece in order to optimize the workpiece characteristics is a state of the art design method for high-performance components. These workpieces can be made of the most qualified materials according to local requirements. However, during machining of material compounds, the different materials have to be considered. This is due to the specific material properties, cutting characteristics, and chip formation mechanisms. Cutting parameters have to be adapted for each material in order to achieve the demanded workpiece quality and optimal processes in respect of tool life and material removal rate. The focus of this research is the development of an in-process material identification algorithm. Thus, a cylindrical turning process is investigated for friction welded aluminum/steel shafts (EN-AW6082/20MnCr5). A universal monitoring approach is presented which detects the different materials process-parallel. For this purpose, cutting forces and spindle torque are linked with a dexel-based material removal model to determine monitoring parameters. The design of experiment method is used to validate the approach for various process parameters. Cutting speed and feed velocity are adapted for cylindrical turning operations based on the monitoring algorithm. As a result, material-specific cutting parameters are adjusted during the machining in order to optimize the material removal rate. Based on this approach, further process optimization can be implemented, like the improvement of chip formation, while machining hybrid workpieces.
AB - The combination of different materials in one workpiece in order to optimize the workpiece characteristics is a state of the art design method for high-performance components. These workpieces can be made of the most qualified materials according to local requirements. However, during machining of material compounds, the different materials have to be considered. This is due to the specific material properties, cutting characteristics, and chip formation mechanisms. Cutting parameters have to be adapted for each material in order to achieve the demanded workpiece quality and optimal processes in respect of tool life and material removal rate. The focus of this research is the development of an in-process material identification algorithm. Thus, a cylindrical turning process is investigated for friction welded aluminum/steel shafts (EN-AW6082/20MnCr5). A universal monitoring approach is presented which detects the different materials process-parallel. For this purpose, cutting forces and spindle torque are linked with a dexel-based material removal model to determine monitoring parameters. The design of experiment method is used to validate the approach for various process parameters. Cutting speed and feed velocity are adapted for cylindrical turning operations based on the monitoring algorithm. As a result, material-specific cutting parameters are adjusted during the machining in order to optimize the material removal rate. Based on this approach, further process optimization can be implemented, like the improvement of chip formation, while machining hybrid workpieces.
KW - Hybrid parts
KW - Monitoring
KW - Turning
UR - http://www.scopus.com/inward/record.url?scp=85031943008&partnerID=8YFLogxK
U2 - 10.1007/s00170-017-1196-y
DO - 10.1007/s00170-017-1196-y
M3 - Article
AN - SCOPUS:85031943008
VL - 95
SP - 311
EP - 316
JO - International Journal of Advanced Manufacturing Technology
JF - International Journal of Advanced Manufacturing Technology
SN - 0268-3768
IS - 1-4
ER -