Abstract:Wrinkling and fracture are main defects in sheetmetal forming. They can be reduced or eliminated by manipulating a suitable blank-holder force (BHF). But it is difficult to attain the optimum BHF during sheet-metal forming. In this article, a new optimization algorithm integrating the finite element method (FEM) and adaptive response surface methodology £(r)ARSM£(c) is presented to determinate the optimum BHF. To assure convergence, the trust region modes management strategies are used to adjust the move limit… Show more
“…(STEP3) All functions are approximated by the RBF network; wherein the approximated objective functions are denoted asf i x ð Þ i ¼ 1; 2; ⋯; K ð Þ , and the approximated constraint functions are denoted asg j x ð Þ j ¼ 1; 2; ⋯; ncon ð Þ . (STEP4) A pareto-optimal solution for the response surface is found using the weighted lp norm method formulated as follows (Chengzhi et al 2005):…”
Section: Sequential Approximate Optimization For Multi-objective Optimentioning
confidence: 99%
“…The weighted lp norm method is used to find a paretooptimal solution, and the weight for each objective function should be assigned. Unlike the weighted sum, the weighted lp norm method can find a set of paretooptimal solutions of the non-convex pareto-frontier with various weights (Chengzhi et al 2005). 3.…”
Section: Sequential Approximate Optimization For Multi-objective Optimentioning
confidence: 99%
“…In most cases, a constant BHF through the punch stroke is simply used. By adopting variable BHF (VBHF) approach, in which BHF varies throughout the punch stroke, improvements in the final product quality should be achievable (Chengzhi et al 2005;Lin et al 2007;Kitayama et al 2010). Furthermore, the VBHF is not only useful for reducing the earing in deep drawing, but also for controlling the material flow into the die.…”
Optimal blank shape minimizing earing in deep drawing has a direct influence on material saving as well as product quality. A number of methods for blank shape optimization have been previously proposed, most of which adopt a closed-loop type algorithm that requires a large number of simulation runs. Numerical simulation in sheet metal forming is so numerically intensive that it is preferable to find an optimal blank shape with a small number of simulation runs. This paper proposes a method for determining the optimal blank shape design in square cup deep drawing using sequential approximate optimization (SAO) with a radial basis function (RBF) network. Sheet metal forming is multi-objective in nature, and thus the blank shape design problem is formulated as a multi-objective design optimization. The aim is therefore to identify the pareto-frontier with a small number of simulation runs. The earing is minimized under tearing and wrinkling constraints with a variable blank holder force (VBHF), which varies through the punch stroke. Numerical results show that the disconnected pareto-frontier is well identified with a small number of simulation runs. The earing of the optimal blank shape with the VBHF is also drastically reduced, when compared to a reference blank shape. Based on the numerical results, the experiments using a servo press are carried out. Consequently, the validity of the proposed approach is confirmed through the numerical and experimental results.
“…(STEP3) All functions are approximated by the RBF network; wherein the approximated objective functions are denoted asf i x ð Þ i ¼ 1; 2; ⋯; K ð Þ , and the approximated constraint functions are denoted asg j x ð Þ j ¼ 1; 2; ⋯; ncon ð Þ . (STEP4) A pareto-optimal solution for the response surface is found using the weighted lp norm method formulated as follows (Chengzhi et al 2005):…”
Section: Sequential Approximate Optimization For Multi-objective Optimentioning
confidence: 99%
“…The weighted lp norm method is used to find a paretooptimal solution, and the weight for each objective function should be assigned. Unlike the weighted sum, the weighted lp norm method can find a set of paretooptimal solutions of the non-convex pareto-frontier with various weights (Chengzhi et al 2005). 3.…”
Section: Sequential Approximate Optimization For Multi-objective Optimentioning
confidence: 99%
“…In most cases, a constant BHF through the punch stroke is simply used. By adopting variable BHF (VBHF) approach, in which BHF varies throughout the punch stroke, improvements in the final product quality should be achievable (Chengzhi et al 2005;Lin et al 2007;Kitayama et al 2010). Furthermore, the VBHF is not only useful for reducing the earing in deep drawing, but also for controlling the material flow into the die.…”
Optimal blank shape minimizing earing in deep drawing has a direct influence on material saving as well as product quality. A number of methods for blank shape optimization have been previously proposed, most of which adopt a closed-loop type algorithm that requires a large number of simulation runs. Numerical simulation in sheet metal forming is so numerically intensive that it is preferable to find an optimal blank shape with a small number of simulation runs. This paper proposes a method for determining the optimal blank shape design in square cup deep drawing using sequential approximate optimization (SAO) with a radial basis function (RBF) network. Sheet metal forming is multi-objective in nature, and thus the blank shape design problem is formulated as a multi-objective design optimization. The aim is therefore to identify the pareto-frontier with a small number of simulation runs. The earing is minimized under tearing and wrinkling constraints with a variable blank holder force (VBHF), which varies through the punch stroke. Numerical results show that the disconnected pareto-frontier is well identified with a small number of simulation runs. The earing of the optimal blank shape with the VBHF is also drastically reduced, when compared to a reference blank shape. Based on the numerical results, the experiments using a servo press are carried out. Consequently, the validity of the proposed approach is confirmed through the numerical and experimental results.
“…Thus, the objective of the VBHF approach is to find the VBHF trajectory through the punch stroke. The VBHF approaches can be roughly classified into two categories: One is based on the closed-loop type algorithm and the other is the response surface method (RSM) (7)(8)(9)(10)(11)(12) . The authors have already proposed both approaches for avoiding these defects, and the detailed procedures can be found in Refs.…”
Optimum segmented blank holder shape and its variable blank holder gaps (VBHGs) are determined by a sequential approximate optimization (SAO) with radial basis function network. In deep drawing, wrinkling and tearing of blank sheet are major defects. The optimum segmented blank holder shape and its VBHGs are determined to avoid these defects. The Forming Limit Diagram (FLD) is employed to evaluate quantitatively the wrinkling and the tearing. In the numerical examples, a square cup deep drawing is handled. The objective is to minimize the thickness deviation after sheet forming. The wrinkling and the tearing are separately evaluated as the constraints. The dimensions of the segmented blank holder shape and the BHGs are taken as the design variables. The optimization result shows that simultaneous optimization of both the segmented blank holder shape and the VBHGs is one of the effective approaches for improving product quality.
In deep drawing, a low blank holder force (BHF) will cause wrinkling, while a high BHF will lead to tearing. The Variable Blank Holder Force (VBHF) is an attractive approach in the industries, and it is important to determine the VBHF trajectory. In this paper, a sequential approximate optimization (SAO) approach is employed for determining the VBHF trajectory. The objective is taken as the minimization of the deviation of whole thickness. The constraint is quantitatively defined with the Forming Limit Diagram (FLD), in which no wrinkling and tearing can be observed. The blank holder forces are taken as the design variables. Two constraints in which wrinkling and tearing are avoided are employed in this paper. The Radial Basis Function (RBF) network is employed for constructing the response surface to capture the non-linear phenomena. In the proposed SAO approach, the optimum BHF is added to refine the VBHF trajectory, while some data points are also added to cover the entire design variable space. The result of the VBHF trajectory with the proposed SAO approach is compared with the one of the closed-loop type algorithm.
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