Artificial intelligence approach to predict thinning in the hydroforming process. Issue 2 (2nd April 2016)

• Record Type: Journal Article
• Authors: Yaghoobi, Amirreza; Gorji, Abdolhamid; Bakhshi-Jooybari, Mohammad; Baseri, Hamid
• Is Part Of: Advances in materials and processing technologies. Volume 2:Issue 2(2016)
• Page Start: 252
• Page End: 257
• Publication Date: 2016-04-02
• Subjects: Hydroforming -- sheet hydroforming -- artificial intelligence -- adaptive neuro-fuzzy inference -- ANFIS -- thinning; Materials -- Periodicals; Manufacturing processes -- Periodicals; 620.1105
• DOI: 10.1080/2374068X.2016.1164530
• Languages: English
• ISSNs: 2374-068X

Abstract

Abstract: Fluid pressure path during the hydroforming process has an important effect on the success or failure of the process. Pressure path of the chamber during the process may cause a number of defects such as wrinkling of the flange at the beginning of the process, necking at the unsupported region between the punch and the die and necking at the punch tip. In this study, the application of the artificial intelligence to predict the location and the value of the maximum thickening of the part was studied. An Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed to predict the location and the amount of the maximum thinning in the critical region of the part. Comparison of the predicted values by the ANFIS model and the results of the finite element simulation sufficiently indicated that the ANFIS is accurate and efficient in terms of predicting the location and the value of thinning in the part.