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Research Papers

Selection of Bending Parameters for Minimal Spring-Back Using an ANFIS Model and Simulated Annealing Algorithm

[+] Author and Article Information
H. Baseri1

B. Rahmani, M. Bakhshi-Jooybari

Department of Mechanical Engineering,  Babol Noshirvani University of Technology, P.O. Box 484, Babol, 47148-71167 Iran

1

Corresponding author.

J. Manuf. Sci. Eng 133(3), 031010 (Jun 10, 2011) (7 pages) doi:10.1115/1.4004139 History: Received July 16, 2010; Revised April 20, 2011; Published June 10, 2011; Online June 10, 2011

In this research, a simulated annealing algorithm was used to minimize the spring-back in V-die bending process. First, an adaptive neuro-fuzzy inference system (ANFIS) model was developed using the data generated based on experimental observations. The output parameter of the ANFIS model is spring-back and the input parameters are sheet thickness, sheet orientation, and punch tip radius. The performance of the ANFIS model in training and testing sets is compared with those observations. The results indicated that the ANFIS model can be applied successfully for prediction of spring-back. Then, the ANFIS model was used as a function in simulated annealing algorithm to minimize the spring-back. The results showed that the proposed model has an acceptable performance to optimize the bending process.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

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Figure 4

Flowchart of the simulated annealing implementation

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Figure 5

Structure of the developed ANFIS model

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Figure 6

Comparison of the predicted values by ANFIS network and the experimental results for Gaussian MF and different data set; (a) #1, (b) #2, (c) #3, and (d) #4

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Figure 1

Stress distribution before unloading in bending process, spring-back phenomenon

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Figure 3

Schematic of the ANFIS structure

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