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Petra Wiederkehr (née Kersting)
Petra Wiederkehr (née Kersting)
Verified email at tu-dortmund.de
Title
Cited by
Cited by
Year
Virtual process systems for part machining operations
Y Altintas, P Kersting, D Biermann, E Budak, B Denkena, I Lazoglu
Cirp Annals 63 (2), 585-605, 2014
4762014
A general approach to simulating workpiece vibrations during five-axis milling of turbine blades
D Biermann, P Kersting, T Surmann
CIRP annals 59 (1), 125-128, 2010
1682010
Self-optimizing machining systems
HC Möhring, P Wiederkehr, K Erkorkmaz, Y Kakinuma
CIRP Annals 69 (2), 740-763, 2020
852020
Intelligent fixtures for high performance machining
HC Möhring, P Wiederkehr
Procedia Cirp 46, 383-390, 2016
712016
A testpart for interdisciplinary analyses in micro production engineering
HC Möhring, P Kersting, S Carmignato, JA Yagüe-Fabra, M Maestro, ...
Procedia CIRP 28, 106-112, 2015
482015
Modeling regenerative workpiece vibrations in five-axis milling
K Weinert, P Kersting, T Surmann, D Biermann
Production Engineering 2, 255-260, 2008
482008
Modeling techniques for simulating workpiece deflections in NC milling
P Kersting, D Biermann
CIRP Journal of Manufacturing Science and Technology 7 (1), 48-54, 2014
462014
Optimizing NC-tool paths for simultaneous five-axis milling based on multi-population multi-objective evolutionary algorithms
P Kersting, A Zabel
Advances in Engineering Software 40 (6), 452-463, 2009
462009
Virtual machining: capabilities and challenges of process simulations in the aerospace industry
P Wiederkehr, T Siebrecht
Procedia Manufacturing 6, 80-87, 2016
442016
Experimental and numerical analysis of tribological effective surfaces for forming tools in Sheet-Bulk Metal Forming
P Kersting, D Gröbel, M Merklein, P Sieczkarek, S Wernicke, AE Tekkaya, ...
Production Engineering 10, 37-50, 2016
402016
Simulation concept for predicting workpiece vibrations in five-axis milling
P Kersting, D Biermann
Machining Science and Technology 13 (2), 196-209, 2009
402009
Learning quality characteristics for plastic injection molding processes using a combination of simulated and measured data
F Finkeldey, J Volke, JC Zarges, HP Heim, P Wiederkehr
Journal of Manufacturing Processes 60, 134-143, 2020
352020
Stability prediction in milling processes using a simulation-based Machine Learning approach
A Saadallah, F Finkeldey, K Morik, P Wiederkehr
Procedia CIRP 72, 1493-1498, 2018
352018
Wear behavior of bio-inspired and technologically structured HVOF sprayed NiCrBSiFe coatings
W Tillmann, L Hagen, D Stangier, IA Laemmerhirt, D Biermann, P Kersting, ...
Surface and Coatings Technology 280, 16-26, 2015
352015
Modeling of surface location errors in a multi-scale milling simulation system using a tool model based on triangle meshes
T Siebrecht, P Kersting, D Biermann, S Odendahl, J Bergmann
Procedia CIRP 37, 188-192, 2015
352015
Simulation-based prediction of process forces for grinding free-formed surfaces on machining centers
S Rausch, S Odendahl, P Kersting, D Biermann, A Zabel
Procedia CIRP 4, 161-165, 2012
342012
Stochastic modeling of grain wear in geometric physically-based grinding simulations
P Wiederkehr, T Siebrecht, N Potthoff
CIRP Annals 67 (1), 325-328, 2018
332018
Wear behavior of tribologically optimized tool surfaces for incremental forming processes
P Sieczkarek, S Wernicke, S Gies, AE Tekkaya, E Krebs, P Wiederkehr, ...
Tribology International 104, 64-72, 2016
332016
High-feed milling of tailored surfaces for sheet-bulk metal forming tools
R Hense, C Wels, P Kersting, U Vierzigmann, M Löffler, D Biermann, ...
Production Engineering 9, 215-223, 2015
322015
Real-time prediction of process forces in milling operations using synchronized data fusion of simulation and sensor data
F Finkeldey, A Saadallah, P Wiederkehr, K Morik
Engineering Applications of Artificial Intelligence 94, 103753, 2020
302020
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Articles 1–20