TY - JOUR
T1 - Experimental investigation of springback in air bending process
AU - Alhammadi, Aysha
AU - Rafique, Hafsa
AU - Alkaabi, Meera
AU - Abu Qudeiri, Jaber
N1 - Funding Information:
This project was financially supported by United Arab Emirate University, Summer Undergraduate Research Experience (SURE) PLUS Program
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2018/3/2
Y1 - 2018/3/2
N2 - Bending processes is one of the important processes in sheet metal forming. One of the challenge that faces the air bending process is springback, which happens due to the elastic recovery during unloading stage. An accurate analysis of springback during the bending process is crucial to achieve a required bend angle. This paper will investigate the springback experimentally by changing many parameters such as tested material, die opening, thickness, etc. and finding its effect on the value of springback. Additionally, the paper will investigate the effect of loading time at the end of loading stage on the springback by proposing a multistage bending technique (MBT). In MBT, the loading will stop during loading stage just before the end of this stage and it will restart again shortly after. In this study, three sheet metals with different thickness will be examined, namely stainless steel, aluminium and brass. Artificial neural network (ANN) will be utilized to develop a prediction model to predict springback based on the experimental results.
AB - Bending processes is one of the important processes in sheet metal forming. One of the challenge that faces the air bending process is springback, which happens due to the elastic recovery during unloading stage. An accurate analysis of springback during the bending process is crucial to achieve a required bend angle. This paper will investigate the springback experimentally by changing many parameters such as tested material, die opening, thickness, etc. and finding its effect on the value of springback. Additionally, the paper will investigate the effect of loading time at the end of loading stage on the springback by proposing a multistage bending technique (MBT). In MBT, the loading will stop during loading stage just before the end of this stage and it will restart again shortly after. In this study, three sheet metals with different thickness will be examined, namely stainless steel, aluminium and brass. Artificial neural network (ANN) will be utilized to develop a prediction model to predict springback based on the experimental results.
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U2 - 10.1088/1757-899X/323/1/012021
DO - 10.1088/1757-899X/323/1/012021
M3 - Conference article
AN - SCOPUS:85044524880
SN - 1757-8981
VL - 323
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 1
M1 - 012021
T2 - 1st International Conference on Functional Materials and Chemical Engineering, ICFMCE 2017
Y2 - 24 November 2017 through 26 November 2017
ER -