Bend angle prediction and parameter optimisation for laser bending of stainless steel using FEM and RSM

Venkadeshwaran, K.; Das, S.; Misra, Dipten

doi:10.1504/ijmms.2012.048237

Cited by 3 publications

(3 citation statements)

References 16 publications

(14 reference statements)

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“…To validate the capability of the current simulation, results are compared with published results of (Venkadeshwaran et al, 2012) and (Jung, 2006). The materials used are AISI 304 and Ship-building steel 1.0584 (D36) for validation.…”

Section: Validation Of Finite Element Modelmentioning

confidence: 99%

“…Table 1 summarises the input parameters, the simulation results of temperature field and percentages of error for validation with published work of (Jung, 2006). Table 2 summarises the input parameters, the simulation results of bending angle and percentages of error with published work of (Venkadeshwaran et al, 2012) and (Jung, 2006). Bend angles and thermal fields achieved from the present simulations are found to be in close agreement with those from the both references (Venkadeshwaran et al, 2012) and (Jung, 2006).…”

Section: Validation Of Finite Element Modelmentioning

confidence: 99%

“…They have found that bending angle depends on beam diameter, pulse duration, scan velocity and laser power in diminishing order of significance. (Venkadeshwaran et al, 2012) used FEM and RSM to predict bending angle and optimise process parameters for bending of stainless steel. They have identified optimised parameters to increase productivity, reduce operating cost and HAZ.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Numerical simulation of laser bending of AISI 304 plate with a rectangular cut out

Paramasivan¹,

Das²,

Sundar³

et al. 2017

Int. J. Eng. Sci. Tech

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This paper presents investigation of laser bending of AISI 304 plate having a rectangular cut out at its middle via process modeling by finite element method and statistical techniques. The objective is to study the effects of process and geometric parameters on thermal and deformation fields. Correlations are developed, with satisfactory accuracy, to predict maximum temperature and bending angle in the form of second order equations using response surface methodology. Artificial Neural Network models are also developed to predict maximum temperature and bending angle. Results indicate that maximum temperature and bending angle increases with laser power and decreases with increase in scanning speed. Moreover, bending angle decreases with increase in cut out dimension along laser scanning path due to the reduced interaction time between the work piece and the laser beam. Predictions from regression models and neural network models are compared with simulation results and performance of both approaches are found to be satisfactory.

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Section: Validation Of Finite Element Modelmentioning

confidence: 99%

Section: Validation Of Finite Element Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Numerical simulation of laser bending of AISI 304 plate with a rectangular cut out

Paramasivan¹,

Das²,

Sundar³

et al. 2017

Int. J. Eng. Sci. Tech

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Empirical Modeling and Optimization of Laser Bending Process Parameters using the Central Composite Design Method for HDD Slider PSA/RSA Adjustment

Boonpuang

Mongkolwongroj

Sakulkalavek

et al. 2020

Lasers Manuf. Mater. Process.

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Forward and inverse predictions of deformations in laser forming of shaped surfaces under coupling mechanism

Maji

Pratihar

Nath

2018

Journal of Laser Applications

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This article deals with out-of-plane and in-plane deformations of an American Iron and Steel Institute 304 stainless steel sheet in laser forming under the coupling mechanism, which is required to make any three-dimensional (3D) part from a flat sheet. Experiments were carried out based on face centered central composite design of experiments to develop statistical regression models based on experimental data for both the types of deformations, i.e., in-plane and out-of-plane, as a function of input parameters, such as laser power, scan speed, and spot diameter. Adaptive neuro-fuzzy inference system-based models were also developed to predict bending or out-of-plane and thickening or in-plane deformations. Process synthesis or inverse analysis, that is, to decide the process parameters to laser form a 3D shape from flat sheet metal was performed using an adaptive neuro-fuzzy inference system. Prediction accuracy of the developed models was verified through experiments and good correlation was found in estimating deformations and process parameters for both forward and inverse analyses. The effect of Fourier number on deformation in making a three-dimensional surface was also studied, and it was found to be an important factor in obtaining a three-dimensional shape with desired accuracy.

show abstract

Bend angle prediction and parameter optimisation for laser bending of stainless steel using FEM and RSM

Cited by 3 publications

References 16 publications

Numerical simulation of laser bending of AISI 304 plate with a rectangular cut out

Numerical simulation of laser bending of AISI 304 plate with a rectangular cut out

Empirical Modeling and Optimization of Laser Bending Process Parameters using the Central Composite Design Method for HDD Slider PSA/RSA Adjustment

Forward and inverse predictions of deformations in laser forming of shaped surfaces under coupling mechanism

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