Experimental Prediction of Spring back in U Bending Profile Process Modeling using Artificial Neural Network
S. Saravanan1, M. Saravanan2, D. Jeyasimman3, S. Vidhya4, M. Vairavel5
1S. Saravanan Research Scholar, Department of Mechanical Engineering, Periyar Maniammai Institute of Science & Technology, Vallam, Thanjavur, Tamil Nadu, India.
2M. Saravanan Senior Professor, Department of Mechanical Engineering, Ponjesly College of Engineering, Nagercoil, Tamil Nadu, India.
3D. Jeyasimman Associate Professor, Department of Mechanical Engineering, PeriyarManiammai Institute of Science &Technology,Vallam, Thanjavur, Tamil Nadu, India.
4S. Vidhya UG Student, Department of Mechanical Engineering, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India.
5M. Vairavel Research Scholar, Department of Mechanical Engineering and Science, Vels University, Pallavaram, Tamil Nadu, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 21, 2020. | Manuscript published on March 10, 2020. | PP: 110-115 | Volume-9 Issue-5, March 2020. | Retrieval Number: D1819029420/2020©BEIESP | DOI: 10.35940/ijitee.D1819.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: An ANN or Artificial Neural Network is prototypical that is employed to connect the variety of parameter space. The air bend contains curve force and spring-back. These are predicted through the numerical and semi-logical model. A number of researchers examine these models. A collection of information is fitted by Artificial Neural Network which has high flexibility, the capacity to delineate non-straight connections and parallel usage, collaborations of process parameters, Vigor and the adaptation to non-critical failure are the main characteristics of ANN. Due to these characteristics, and the device of ANN successfully monitors the problems. The significant quality of ANN is that the “U” shaped profile of bending among the information that is involved in the associations of parameters and mind-boggling and the sheet metals bend researchers.
Keywords: FEM, Spring Back, Bouncing Error
Scope of the Article: Application Artificial Intelligence and Machine Learning in the Field of Network and Database