TY - GEN A1 - Imran, Muhammad A1 - Bambach, Markus ED - Fratini, Livan ED - Di Lorenzo, Rosa ED - Buffa, Gianluca ED - Ingarao, Guiseppe T1 - Towards the damage evaluation using Gurson-Tvergaard-Needleman (GTN) model for hot forming processes T2 - Proceedings of the 21st International ESAFORM Conference on Material Forming, ESAFORM 2018, Palermo, Italy, 23-25 April 2018 Y1 - 2018 SN - 978-0-7354-1663-5 U6 - https://doi.org/10.1063/1.5035063 PB - AIP Publishing CY - Melville, New York ER - TY - GEN A1 - Ünsal, Ismail A1 - Hama-Saleh, Rebar A1 - Sviridov, Alexander A1 - Bambach, Markus A1 - Weisheit, Andreas A1 - Schleifenbaum, Johannes Henrich T1 - Mechanical properties of sheet metal components with local reinforcement produced by additive manufacturing T2 - Proceedings of the 21st International ESAFORM Conference on Material Forming, ESAFORM 2018, Palermo, Italy, 23-25 April 2018 Y1 - 2018 SN - 978-0-7354-1663-5 U6 - https://doi.org/10.1063/1.5035054 PB - AIP Publishing CY - Melville, New York ER - TY - GEN A1 - Conte, Romina A1 - Buhl, Johannes A1 - Ambrogio, Giuseppina A1 - Bambach, Markus ED - Fratini, Livan ED - Di Lorenzo, Rosa ED - Buffa, Gianluca ED - Ingarao, Guiseppe T1 - Joining of aluminum sheet and glass fiber reinforced polymer using extruded pins T2 - Proceedings of the 21st International ESAFORM Conference on Material Forming, ESAFORM 2018, Palermo, Italy, 23-25 April 2018 Y1 - 2018 SN - 978-0-7354-1663-5 U6 - https://doi.org/10.1063/1.5034881 PB - AIP Publishing CY - Melville, New York ER - TY - GEN A1 - Klusemann, Benjamin A1 - Bambach, Markus ED - Fratini, Livan ED - Di Lorenzo, Rosa ED - Buffa, Gianluca ED - Buffa, Gianluca T1 - Stability of phase transformation models for Ti-6Al-4V under cyclic thermal loading imposed during laser metal deposition T2 - Proceedings of the 21st International ESAFORM Conference on Material Forming, ESAFORM 2018, Palermo, Italy, 23-25 April 2018 Y1 - 2018 SN - 978-0-7354-1663-5 U6 - https://doi.org/10.1063/1.5035004 PB - AIP Publishing CY - Melville, New York ER - TY - GEN A1 - Nguyen, Lam A1 - Buhl, Johannes A1 - Bambach, Markus T1 - Decomposition algorithm for tool path planning for wire-arc additive manufacturing T2 - Journal of Machine Engineering Y1 - 2018 U6 - https://doi.org/10.5604/01.3001.0010.8827 SN - 1895-7595 SN - 2391-8071 VL - 18 IS - 1 SP - 96 EP - 107 ER - TY - GEN A1 - Fergani, Omar A1 - Bratli, Wold A. A1 - Berto, F. A1 - Brotan, Vegard A1 - Bambach, Markus T1 - Study of the effect of heat treatment on fatigue crack growth behaviour of 316L stainless steel produced by selective laser melting T2 - Fatigue & Fracture of Engineering Materials & Structures Y1 - 2018 U6 - https://doi.org/10.1111/ffe.12755 SN - 1460-2695 VL - 41 IS - 5 SP - 1102 EP - 1119 ER - TY - GEN A1 - Yang, D. Y. A1 - Bambach, Markus A1 - Cao, J. A1 - Duflou, J. R. A1 - Groche, P. A1 - Kuboki, T. A1 - Sterzing, A. A1 - Tekkaya, A. Erman A1 - Lee, C. W. T1 - Flexibility in metal forming T2 - CIRP Annals N2 - Flexibility in metal forming is needed more than ever before due to rapidly changing customer demands. It paves the way for a better control of uncertainties in development and application of metal forming processes. Although flexibility has been pursued from various viewpoints in terms of machines, material, process, working environment and properties, etc., a thorough study of the concept was undertaken in order to with problems of manufacturing competiveness and tackle new challenges of manufacturing surroundings. Therefore, in this paper, flexibility in forming is reviewed from the viewpoints of process, material, manufacturing environment, new process combinations and machine–system–software interactions. Y1 - 2018 U6 - https://doi.org/10.1016/j.cirp.2018.05.004 SN - 0007-8506 VL - 67 IS - 2 SP - 743 EP - 765 ER - TY - GEN A1 - Maqbool, Fawad A1 - Bambach, Markus T1 - Dominant deformation mechanisms in single point incremental forming (SPIF) and their effect on geometrical accuracy T2 - International Journal of Mechanical Sciences Y1 - 2018 U6 - https://doi.org/10.1016/j.ijmecsci.2017.12.053 SN - 0020-7403 VL - 136 SP - 279 EP - 292 ER - TY - GEN A1 - Bambach, Markus A1 - Sizova, Irina A1 - Silze, Frank A1 - Schnick, Michael T1 - Comparison of laser metal deposition of Inconel 718 from powder, hot and cold wire T2 - Procedia CIRP N2 - 10th CIRP conference on Photonic Technologies LANE 2018, September 03 - 06, 2018, Fürth, Germany Y1 - 2018 U6 - https://doi.org/10.1016/j.procir.2018.08.095 SN - 2212-8271 VL - 74 SP - 206 EP - 209 ER - TY - GEN A1 - Bambach, Markus A1 - Sizova, Irina A1 - Emdadi, Aliakbar T1 - Towards Damage Controlled Hot Forming T2 - Applied Mechanics and Materials Y1 - 2018 U6 - https://doi.org/10.4028/www.scientific.net/AMM.885.56 SN - 1662-7482 VL - 85 SP - 56 EP - 63 ER - TY - GEN A1 - Bambach, Markus A1 - Sizova, Irina A1 - Emdadi, Aliakbar T1 - Development of a processing route for Ti-6Al-4V forgings based on preforms made by selective laser melting T2 - Journal of Manufacturing Processes Y1 - 2019 U6 - https://doi.org/10.1016/j.jmapro.2018.11.011 SN - 1526-6125 SN - 0278-6125 VL - 37 SP - 150 EP - 158 ER - TY - GEN A1 - Hart-Rawung, Thawin A1 - Buhl, Johannes A1 - Bambach, Markus T1 - Extension of a phase transformation model for partial hardening in hot stamping T2 - Journal of Machine Engineering Y1 - 2018 U6 - https://doi.org/10.5604/01.3001.0012.4619 SN - 1895-7595 SN - 2391-8071 VL - 18 IS - 3 SP - 87 EP - 97 ER - TY - GEN A1 - Bambach, Markus A1 - Sizova, Irina A1 - Geisen, Ole A1 - Fergani, Omar T1 - Comparison of the Hot Working Behavior of Wrought, Selective Laser Melted and Electron Beam Melted Ti-6Al-4V T2 - Materials Science Forum; Trans Tech Publications Y1 - 2018 U6 - https://doi.org/10.4028/www.scientific.net/MSF.941.2030 SN - 1662-9752 VL - 941 SP - 2030 EP - 2036 ER - TY - GEN A1 - Imran, Muhammad A1 - Afzal, Muhammad Junaid A1 - Bambach, Markus T1 - Analysis of competition between onset of dynamic recrystallization and damage nucleation during hot forming T2 - NUMIFORM 2019: The 13th International Conference on Numerical Methods in Industrial Forming Processes Y1 - 2019 UR - http://www.programmaster.org/PM/PM.nsf/ApprovedAbstracts/8A21E11BABCC7A4F852583460038CCA3?OpenDocument SN - 978-0-87339-769-8 SP - 231 EP - 234 ER - TY - GEN A1 - Santhanakrishnan Balakrishnan, Venkateswaran A1 - Hart-Rawung, Thawin A1 - Buhl, Johannes A1 - Seidlitz, Holger A1 - Bambach, Markus T1 - Impact and damage behaviour of FRP-metal hybrid laminates made by the reinforcement of glass fibers on 22MnB5 metal surface T2 - Composites Science and Technology Y1 - 2020 U6 - https://doi.org/10.1016/j.compscitech.2019.107949 SN - 1879-1050 SN - 0266-3538 VL - Vol. 187 ER - TY - GEN A1 - Imran, Muhammad A1 - Szyndler, Joanna A1 - Afzal, Muhammad Junaid A1 - Bambach, Markus T1 - Dynamic recrystallization-dependent damage modeling during hot forming T2 - International Journal of Damage Mechanics Y1 - 2020 U6 - https://doi.org/10.1177/1056789519848477 SN - 1530-7921 VL - 29 IS - 2 SP - 335 EP - 363 ER - TY - GEN A1 - Bambach, Markus A1 - Imran, Muhammad T1 - Extended Gurson–Tvergaard–Needleman model for damage modeling and control in hot forming T2 - Cirp Annals - Manufacturing Technology Y1 - 2019 U6 - https://doi.org/10.1016/j.cirp.2019.04.063 SN - 0007-8506 VL - 68 IS - 1 SP - 249 EP - 252 ER - TY - GEN A1 - Stendal, Johan Andreas A1 - Bambach, Markus A1 - Eisentraut, Mark A1 - Sizova, Irina A1 - Weiß, Sabine T1 - Applying Machine Learning to the Phenomenological Flow Stress Modeling of TNM-B1 T2 - Metals N2 - Data-driven or machine learning approaches are increasingly being used in material science and research. Specifically, machine learning has been implemented in the fields of materials discovery, prediction of phase diagrams and material modelling. In this work, the application of machine learning to the traditional phenomenological flow stress modelling of the titanium aluminide (TiAl) alloy TNM-B1 (Ti-43.5Al-4Nb-1Mo-0.1B) is investigated. Three model types were developed, analyzed and compared; a physics-based phenomenological model (PM) originally developed for steel by Cingara and McQueen, a purely data-driven machine learning model (MLM), and a hybrid model (HM), which uses characteristic points predicted by a learning algorithm as input for the phenomenological model. The same amount of data was used to both fit the PM and train the MLM and HM. The models were analyzed and compared based on the accuracy of their predictions, development and computing time, and their ability to predict on interpolated and extrapolated inputs. The results revealed that for the same amount of experimental data, the MLM was more accurate than the PM. In addition, the MLM was better able to capture the characteristic peak stress in the TNM-B1 the flow curves, and could be developed and computed faster. Furthermore, the MLM was able to make realistic predictions for inputs outside the experimental data used for training. The HM showed comparable accuracy to the PM for the experimental conditions. However, the HM was able to produce a better fit for input conditions outside the training data. KW - machine learning KW - phenomenological modeling KW - titanium aluminide KW - hot isothermal forging Y1 - 2019 UR - https://www.mdpi.com/2075-4701/9/2/220 U6 - https://doi.org/10.3390/met9020220 SN - 2075-4701 VL - 9 IS - 2 ER -