Single-point incremental forming of sheet metals: Experimental study and numerical simulation

2016 ◽  
Vol 231 (2) ◽  
pp. 301-312 ◽  
Author(s):  
Matteo Benedetti ◽  
Vigilio Fontanari ◽  
Bernardo Monelli ◽  
Marco Tassan
Keyword(s):  
Numerical Simulation ◽  
Finite Element ◽  
Incremental Forming ◽  
Single Point ◽  
Integration Scheme ◽  
Al Alloy ◽  
Single Point Incremental Forming ◽  
Sheet Metals ◽  
Forming Process ◽  
Starting Point

In this article, the single-point incremental forming of sheet metals made of micro-alloyed steel and Al alloy is investigated by combining the results of numerical simulation and experimental characterization, performed during the process, as well as on the final product. A finite element model was developed to perform the process simulation, based on an explicit dynamic time integration scheme. The finite element outcomes were validated by comparison with experimental results. In particular, forming forces during the process, as well as the final shape and strain distribution on the finished component, were measured. The obtained results showed the capability of the finite element modelling to predict the material deformation process. This can be considered as a starting point for the reliable definition of the single-point incremental forming process parameters, thus avoiding expensive trial-and-error approaches, based on extensive experimental campaigns, with beneficial effects on production time.

Numerical Simulation for the Multi-Point Incremental Forming Process

2015 ◽  
Vol 775 ◽  
pp. 219-223
Author(s):  
Wan Mian Yang ◽  
Yuan Xin Luo ◽  
Zhi Fang Liu ◽  
Ru Xu Du
Keyword(s):  
Numerical Simulation ◽  
Finite Element ◽  
Finite Element Model ◽  
Sheet Metal ◽  
Incremental Forming ◽  
Element Model ◽  
Sheet Metals ◽  
Forming Force ◽  
Forming Process ◽  
Thickness Change

Multi-point forming process has been developed to shape the sheet metal with bidirectional curvature. However, the forming force usually climbs too high so that the dimension of the forming machine should be designed to meet it. To solve this problem, the multi-point incremental forming (MPIF) process was proposed in this paper. First, the principle of this new forming process was introduced. Then, the experimental device was designed. Next, the MPIF process was simulated by a finite element model. The forming effects including displacements, thickness, and curvatures were visualized and discussed in detail. It was found that there is no obvious thickness change during the forming process. The advantage of this forming process is that the shape of the sheet metals adaptable and controllable with small forming force.

scholarly journals Formability and Failure Evaluation of AA3003-H18 Sheets in Single-Point Incremental Forming Process through the Design of Experiments

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 808
Author(s):  
Mohanraj Murugesan ◽  
Dong Won Jung
Keyword(s):  
Design Of Experiments ◽  
Incremental Forming ◽  
Single Point ◽  
Al Alloy ◽  
Single Point Incremental Forming ◽  
Forming Process ◽  
Step Size ◽  
Response Variable ◽  
Test Conditions ◽  
Grey Relational

The single-point incremental forming process (SPIF) is one of the emerging manufacturing methods because of its flexibility in producing the desired complex shapes with higher formability at low-cost compared to traditional sheet forming methods. In this research work, we experimentally investigate the forming process to determine the influence of process parameters and their contribution to enhancing the formability without causing a fracture by combining the design of experiments (DOE), grey relational analysis (GRA), and statistical analysis of variance (ANOVA). The surface morphology and the energy dispersive X-ray spectroscopy (EDS) method are used to perform elemental analysis and examine the formed parts during three forming stages. The DOE procedure, a central composite design with a face-centered option, is devised for AA3003-H18 Al alloy sheet for modeling the real-time experiments. The response surface methodology (RSM) approach is adopted to optimize the forming parameters and recognize the optimal test conditions. The statistically developed model is found to have agree with the test measurements. The prediction model’s capability in R2 is computed as 0.8931, indicating that the fitted regression model adequately aligns with the estimated grey relational grade (GRG) data. Other statistical parameters, such as root mean square error (RMSE) and average absolute relative error (AARE), are estimated as 0.0196 and 2.78%, respectively, proving the proposed regression model’s overall closeness to the measured data. In addition, the prediction error range is identified as −0.05 to 0.05, which is significantly lower and the residual data are distributed normally in the design space with variance and mean of 3.3748 and −0.1232, respectively. ANOVA is performed to understand the adequacy of the proposed model and the influence of the input factors on the response variable. The model parameters, including step size, feed rate, interaction effect of tool radius and step size, favorably influence the response variable. The model terms X2 (0.020 and 11.30), X3 (0.018 and 12.16), and X1X2 (0.026 and 9.72) are significant in terms of p-value and F-value, respectively. The microstructural inspection shows that the thinning behavior tends to be higher as forming depth advances to its maximum; the deformation is uniform and homogeneous under the predefined test conditions.

Geometry Compensation Methods for Increasing the Accuracy of the SPIF Process

2021 ◽  
Vol 883 ◽  
pp. 217-224
Author(s):  
Yannick Carette ◽  
Marthe Vanhulst ◽  
Joost R. Duflou
Keyword(s):  
Control Strategy ◽  
Incremental Forming ◽  
Single Point ◽  
Single Point Incremental Forming ◽  
Calculation Methods ◽  
Forming Process ◽  
Complex Deformation ◽  
Commercial Use ◽  
Compensation Methods ◽  
Deformation Mechanics

Despite years of supporting research, commercial use of the Single Point Incremental Forming process remains very limited. The promised flexibility and lack of specific tooling is contradicted by its highly complex deformation mechanics, resulting in a process that is easy to implement but where workpiece accuracy is very difficult to control. This paper looks at geometry compensation as a viable control strategy to increase the accuracy of produced workpieces. The input geometry of the process can be compensated using knowledge about the deformations occurring during production. The deviations between the nominal CAD geometry and the actual produced geometry can be calculated in a variety of different ways, thus directly influencing the compensation. Two different alignment methods and three deviation calculation methods are explained in detail. Six combined deviation calculation methods are used to generate compensated inputs, which are experimentally produced and compared to the uncompensated part. All different methods are able to noticeably improve the accuracy, with the production alignment and closest point deviation calculation achieving the best results

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