An experimental study on the examination of springback of sheet metals with several thicknesses and properties in bending dies

Tekıner, Zafer

doi:10.1016/j.jmatprotec.2003.07.005

Cited by 129 publications

(85 citation statements)

References 12 publications

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“…During bending processes, it is seen that waiting time and material thicknesses are effective on spring-back [4][5][6]. The effect of material thickness on bending processes was reported in previous studies [7]. Studies are also increasing on the spring-back and -go amounts in V bending processes [8][9][10][11].…”

Section: Introductionsupporting

confidence: 51%

Microstructural Characterization and Deformation of X10CrAlSi24 Sheet Material Applied V-Bending Process

Özdemir

Gökmeşe

2018

Teh. vjesn.

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This study used X10CrAlSi24 (1.4762) sheet material, which is widespread in bending processes of the energy sector. During bending of X10CrAlSi24 (1.4762) sheet materials, cracking and tearing occur due to these materials' brittleness at room temperatures. To avoid this phenomenon, bending was carried out by applying normalization treatments at 800 ºC, 850 ºC, 900 ºC and 950 ºC. V-bending processes were performed at three different bending angles (30º, 60º, 90º) and by a 4.5 mm punch tip radius. V-bending processes were carried out without leaving the punch on the material, and crushing of the punch on the sheet material sectional area was allowed. As a result of the bending processes, spring-go occurred in the 30º and 60º bending applications, whereas spring-back occurred in the 90º bending applications. The formation mechanism of capillary cracks (depending on deformation) due to internal stress especially at low temperatures was introduced by the microstructural characterization of the specimens.

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Section: Introductionsupporting

confidence: 51%

Microstructural Characterization and Deformation of X10CrAlSi24 Sheet Material Applied V-Bending Process

Özdemir

Gökmeşe

2018

Teh. vjesn.

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“…As the comprehensive influence of the system error on parts' dimension, dimensional deviation is the essential prerequisite for evaluating or improving the manufacturing process. Taking the molded parts as an example, part dimensional deviation is the basis of the reverse adjustment of the mold cavity [8,9]. However, it is impossible to measure all parts and then calculate its dimensional deviation due to the high cost.…”

Section: Introductionmentioning

confidence: 99%

Dimensional Deviation Estimation for Parts with Free-Form Surfaces

Zhao

Wang

Zhou

et al. 2018

Mathematical Problems in Engineering

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Dimensional deviation is a prerequisite for improving the manufacturing process of parts with free-form surfaces, for example, the reverse adjustment of the die cavity of turbine blade. Influenced by random noise of the manufacturing process, dimensional variation is inevitable for batch parts. Therefore, it may cause unacceptable error to estimate batch parts dimensional deviation by a single sample. Meanwhile, the optimum sample size for estimating dimensional deviation is difficult to determine. To overcome this problem, a practical method for estimating of dimensional deviation of parts with free-form surface is proposed. Firstly, displacements of the discrete points on part surface are employed to represent dimensional error of the part. Estimating dimensional deviation of parts is actually to estimate the simultaneous confidence intervals of the discrete point displacements. Secondly, Bonferroni simultaneous confidence intervals are adopted to estimate the confidence intervals of the part dimensional deviation. Moreover, the accuracy of the estimation will be continuously improved by increasing samples. Consequently, a practical dimensional deviation estimation method is presented. Finally, a compressor blade is adopted to illustrate the proposed method. The percentage of estimation error of the blade dimensional deviation that is less than 0.05mm, which is the estimation error limit, of all the 100 times sampling experiments is 99%, exceeding the given confidence level of 95%, while the percentage of the existing method is below the confidence level, only 87%.

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“…In recent years, the laser forming process has reached a considerable importance as promising technology in many manufacturing domains, such as automobile, microelectronics and aerospace [1][2][3][4]. The laser forming process has many advantages.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy model for Laser Assisted Bending Process

Giannini

Guarino

2016

MATEC Web of Conferences

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Abstract. In the present study, a fuzzy model was developed to predict the residual bending in a conventional metal bending process assisted by a high power diode laser. The study was focused on AA6082T6 aluminium thin sheets. In most dynamic sheet metal forming operations, the highly nonlinear deformation processes cause large amounts of elastic strain energy stored in the formed material. The novel hybrid forming process was thus aimed at inducing the local heating of the mechanically bent workpiece in order to decrease or eliminate the related springback phenomena. In particular, the influence on the extent of springback phenomena of laser process parameters such as source power, scan speed and starting elastic deformation of mechanically bent sheets, was experimentally assessed. Consistent trends in experimental response according to operational parameters were found. Accordingly, 3D process maps of the extent of the springback phenomena according to operational parameters were constructed. The effect of the inherent uncertainties on the predicted residual bending caused by the approximation in the model parameters was evaluated. In particular, a fuzzy-logic based approach was used to describe the model uncertainties and the transformation method was applied to propagate their effect on the residual bending.

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An experimental study on the examination of springback of sheet metals with several thicknesses and properties in bending dies

Cited by 129 publications

References 12 publications

Microstructural Characterization and Deformation of X10CrAlSi24 Sheet Material Applied V-Bending Process

Microstructural Characterization and Deformation of X10CrAlSi24 Sheet Material Applied V-Bending Process

Dimensional Deviation Estimation for Parts with Free-Form Surfaces

Fuzzy model for Laser Assisted Bending Process

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