Design of a sensor for on-line measurement of loaded bend angle for pressbrake control

Controlling springback in small radius pressbrake bending operations is motivated by the need to produce small lot parts of high quality. A new technique for springback control has been developed based on a simplified analytic model of material and tooling geometry variables. This technique requires the on-line measurement of loaded angle with a robust, high resolution optical sensor which is insensitive to material surface finish. The design of the sensor minimizes systematic error due to placement on the press bed. Loaded angle measurement accuracy of less than one arc minute is achieved. In combination with a press ram position control scheme, this sensor provides a more accurate bending process necessary for the further development of precision, small-lot sheet metal assembly manufacture.     

Deep Learning in Sheet Metal Bending With a Novel Theory-Guided Deep Neural Network

Sheet metal forming technologies have been intensively studied for decades to meet the increasing demand for lightweight metal components. To surmount the springback occurring in sheet metal forming processes, numerous studies have been performed to develop compensation methods. However, for most existing methods, the development cycle is still considerably time-consumptive and demands high computational or capital cost. In this paper, a novel theory-guided regularization method for training of deep neural networks (DNNs), implanted in a learning system, is introduced to learn the intrinsic relationship between the workpiece shape after springback and the required process parameter, e.g., loading stroke, in sheet metal bending processes. By directly bridging the workpiece shape to the process parameter, issues concerning springback in the process design would be circumvented. The novel regularization method utilizes the well-recognized theories in material mechanics, Swift’s law, by penalizing divergence from this law throughout the network training process. The regularization is implemented by a multi-task learning network architecture, with the learning of extra tasks regularized during training. The stress-strain curve describing the material properties and the prior knowledge used to guide learning are stored in the database and the knowledge base, respectively. One can obtain the predicted loading stroke for a new workpiece shape by importing the target geometry through the user interface. In this research, the neural models were found to outperform a traditional machine learning model, support vector regression model, in experiments with different amount of training data. Through a series of studies with varying conditions of training data structure and amount, workpiece material and applied bending processes, the theory-guided DNN has been shown to achieve superior generalization and learning consistency than the data-driven DNNs, especially when only scarce and scattered experiment data are available for training which is often the case in practice. The theory-guided DNN could also be applicable to other sheet metal forming processes. It provides an alternative method for compensating springback with significantly shorter development cycle and less capital cost and computational requirement than traditional compensation methods in sheet metal forming industry.      

Comparison of regression and artificial neural network model for the prediction of springback during air bending process of interstitial free steel sheet

This paper compares the regression and neural network modeling for predicting springback of interstial free steel sheet during air bending process. In this investigation, punch travel, strain hardening exponent, punch radius, punch velocity and width of the sheet were considered as input variables and springback as response variable. It has been observed that the ANN modeling process has been able to predict the springback with higher accuracy when compared with regression model.     

口腔正畸弓丝矫治器自动制备成形中的 回弹补偿方法

在传统的口腔正畸临床治疗中,弓丝矫治器主要依赖于正畸医师手工弯制来完成,这不仅要求医师有长时间的训练过程,同时难以达到理想的个性化及精度要求,也增加了患者复诊次数及椅旁等待时间。据此,我们研发机器人系统来实现自动化的正畸弓丝矫治器制备。其中的一个难点问题是,弓丝材料的高弹性引起的回弹现象严重影响了弓丝矫治器的成形精度。因此,提出一种基于过弯预补偿模型和回弹力在线检测的过弯补偿方法,来消除弯制过程中的弓丝回弹现象。该方法首先通过一个自行设计的弯制回弹装置测量回弹前后的角度差,并将回弹后的角度作为目标成形角,以此建立成形角过弯量预补偿模型;然后通过力传感器进行弓丝回弹力在线检测,建立基于零力状态判断的自动弯制控制方法。上述方法在所研发的弓丝弯制机器人系统中进行弯制实验测试。结果表明,它能够最大限度地减小回弹效应,实现满足临床精度要求的正畸弓丝自动弯制成形。     

Assessment of sheet-metal bending requirements using neural networks

The springback behaviour of a sheet-metal is dependent on the properties of the metal and the bending conditions, namely the thickness of the sheet-metal, geometry of the tooling and the amount of force used for bending. Sheet-metal component manufacturing often requires near zero springback angle to obtain the correct shape of the product. An attempt has been made to model the non-linear relation between properties of the metal, the springback angle, geometry of the tooling and the bending force applied. Multilayer perceptron neural networks with a backpropagation learning algorithm were used to model the bending process. One set of data from bending experiments in a laboratory environment was used to train the networks. The networks were tested with the remaining set of experimental results. Then, the neural networks were used to predict the forces required for a number of bending experiments to achieve a zero springback angle. Validation of the neural network predictions was performed by trying to apply the predicted amounts of bending force in the physical experiments. The springback angles achieved were within ±1 degree, which is an acceptable range for the work. The research clearly demonstrates the applicability of neural networks to modelling the sheet-metal bending process.     

Response surface methodology for design of sheet forming parameters to control springback effects

This paper deals with the optimization of tools geometry in sheet metal forming in order to reduce the springback effects after forming. A response surface method (RSM) based on diffuse approximation is used; this technique has been proved more efficient than classical gradient based methods since it requires fewer iterations and convergence is guaranteed especially for nonlinear problems. A new improved Inverse Approach for the stamping simulation based on DKTRF shell element is presented. In the new version, the strains and stresses due to bending and unbending effects are calculated analytically from the final workpiece, especially on the die entrance radii for curvature changes. The bending/unbending moments and the final shape are used to calculate springback using a second incremental Approach based on the Updated Lagrangian Formulation. The benchmark on the “U” bending problem of NUMISHEET’93 has been used to validate the method, good results on the elimination of springback have been obtained. The final results are validated using STAMPACK^® and ABAQUS^® commercial codes.     

Springback equation of small curvature plane bending

A new analytical method for springback of small curvature plane bending is addressed with unloading rule of classical elastic-plastic theory and principle of strain superposition.We start from strain analysis of plane bending which has initial curvature,and the theoretic derivation is on the widely applicable basic hypotheses.The results are unified to geometry constraint equations and springback equation of plane bending,which can be evolved to straight beam plane bending and pure bending.The expanding and...     

Springback adjustment for multi-point forming of thick plates in shipbuilding

At most shipyards, flame bending has been widely used to fabricate curved shells. Since residual deformation of flame bending is produced by thermo-elastic-plastic strains, it is difficult to accurately achieve the desired shape. Therefore, mechanical bending processes such as multi-press forming and multi-point press forming have become attractive because such processes can accurately control the desired shape. Springback is one of the major problems associated with mechanical bending. When the pressing tools are removed after the loading stage, the workpiece springs back due to the elastic recovery and the shape deviation needs to be compensated. The tools of the press forming process therefore need to be changed in order for the produced surface to reach the desired shape accurately after springback. Generally, forming tools are designed and constructed to operate through an iterative process in which the die and the pistons are adjusted to compensate for springback after a pressing operation. Such adjustments require significant time and effort. Therefore, the present study investigates not only how to simulate springback deformation, but also the degree of adjustment required to the stroke of pistons in multi-press forming. Finite Element Analysis (FEA) of thick metal forming and an iterative displacement adjustment algorithm are integrated for practical application. Shape deviations between the design surface and the deformed plate are minimized to reach the desired shape.     

JSTAMP/NV在冲压模具开发中的应用

介绍JSTAMP/NV在冲压模具开发过程中前期、中期和后期等3个阶段的应用和实例,详细阐述对仿真有重要影响的因素,包括坯料网格划分、材料模型、仿真速度和回弹及其回弹补偿精度等.JSTAMP/NV能够减少冲压模具开发成本并缩短开发周期.     

Effect of cold bending and welding on buckling of ring-stiffened cylinders

The BOSOR5 computer program for elastic plastic buckling of shells of revolution is used for calculation of bifurcation buckling of cold bent and welded ring-stiffened cylinders under external pressure. Residual stresses and deformations from cold bending and welding are included in the model for buckling under service loads by introduction of these manufacturing processes as functions of a time-like parameter which ensures that the material in the analytical model experiences the proper sequence of loading prior to and during application of the service loads. The cold bending process is first simulated by a thermal loading cycle in which the temperature varies linearly through the shell wall thickness, initially increasing in time to simulate cold bending around a die and then decreasing in time to simulate springback to a final somewhat larger design radius. The welding process is subsequently simulated by the assumption that the material in the immediate neighborhoods of the welds is cooled below the ambient temperature by an amount that leads to weld shrinkage amplitudes typical of those observed in tests. Buckling loads are calculated for a configuration including and neglecting the cold bending and welding processes. These predictions are compared to values obtained from tests on two nominally identical specimens, one carefully machined and the other fabricated by cold bending the shell and then welding machined ring stiffeners to it.     

Optimal process design of sheet metal forming for minimum springback via an integrated neural network evolutionary algorithm

The process of sheet metal forming is characterized by various process parameters. Accurate prediction of springback is essential for the design of tools used in sheet metal forming operations. In this paper, an evolutionary algorithm is presented that is capable of handling single/multiobjective, unconstrained and constrained formulations of optimal process design problems. To illustrate the use of the algorithm, a relatively simple springback minimization problem (hemispherical cup-drawing) is solved in this paper, and complete formulations of the algorithm are provided to deal with the constraints and multiple objectives. The algorithm is capable of generating multiple optimal solutions in a single run. The evolutionary algorithm is combined with the finite element method for springback computation, in order to arrive at the set of optimal process parameters. To reduce the computational time required by the evolutionary algorithm due to actual springback computations via the finite element method, a neural network model is developed and integrated within the evolutionary algorithm as an approximator. The results clearly show the viability of the use of the evolutionary algorithm and the use of approximators to derive optimal process parameters for metal forming operations.     

Optimization of variable blank holder force trajectory for springback reduction via sequential approximate optimization with radial basis function network

Springback is one of the major defects in sheet metal forming. Variable blank holder force (VBHF) approach is one of the effective ways for the springback reduction. In this paper, the VBHF trajectory is optimized to reduce the springback by a sequential approximate optimization (SAO) with radial basis function (RBF) network. The U-shaped forming in NUMISHEET’93 is employed to determine an optimum VBHF trajectory, for example. In this paper, the bending moment is taken as the objective function. The tearing of sheet during the forming is considered as the design constraint, and the forming limit diagram (FLD) is employed to evaluate the design constraint quantitatively. It has been found from numerical results that the optimal VBHF trajectory can drastically reduce the springback in comparison with various VBHF trajectories. Through the theoretical examination and numerical simulation, the springback reduction of metal forming by the VBHF trajectory is discussed.     

KBS-aided design of tube bending processes

Cold bending of metal tube products is a metal forming process widely used in industry. With today's demand on high quality tube-dependent products, bending of tubing parts has become a precision metalworking operation that requires sophisticated knowledge and experience. In this work, a knowledge-based system (KBS) has been developed to aid the design of tube bending processes, including bending methods selection, tool/die design, and process parameters setup. The object-oriented programming techniques and the goal-driven search mechanism, featured by an interactive graphic user interface, have been applied in development of the proposed KBS. The system developed has shown effective in tube parts production with significantly reduced number of potential defects and failures, such as inaccuracy of bend angles or linear dimensions, wall thinning, flattening, wrinkling, twisting, dents or cracks, etc.     

基于闭环控制系统的模具修正算法研究

模具加工中的回弹补偿是一个复杂的过程,利用传统的修正方法很难实现对模具生产环节回弹的有效控制。为提高产品的质量和精度,提出了一种基于闭环控制系统的模具修正模型。针对传统方法无法有效控制的回弹环节,结合时-频变换思想,利用闭环控制系统的误差函数来求解控制系统形状传递函数,通过形状传递函数来计算模具型面形状。仿真结果表明,通过改进的闭环控制系统模具修正模型,可以在相同工艺条件下,正确预测与理想产品相对应的理想模具型面形状,从而达到对回弹误差的有效补偿,修正模具型面的目的。     

Novel soft bending actuator-based power augmentation hand exoskeleton controlled by human intention

This article presents the development of a soft material power augmentation wearable robot using novel bending soft artificial muscles. This soft exoskeleton was developed as a human hand power augmentation system for healthy or partially hand disabled individuals. The proposed prototype serves healthy manual workers by decreasing the muscular effort needed for grasping objects. Furthermore, it is a power augmentation wearable robot for partially hand disabled or post-stroke patients, supporting and augmenting the fingers’ grasping force with minimum muscular effort in most everyday activities. This wearable robot can fit any adult hand size without the need for any mechanical system changes or calibration. Novel bending soft actuators are developed to actuate this power augmentation device. The performance of these actuators has been experimentally assessed. A geometrical kinematic analysis and mathematical output force model have been developed for the novel actuators. The performance of this mathematical model has been proven experimentally with promising results. The control system of this exoskeleton is created by hybridization between cascaded position and force closed-loop intelligent controllers. The cascaded position controller is designed for the bending actuators to follow the fingers in their bending movements. The force controller is developed to control the grasping force augmentation. The operation of the control system with the exoskeleton has been experimentally validated. EMG signals were monitored during the experiments to determine that the proposed exoskeleton system decreased the muscular efforts of the wearer.     

自适应模糊神经网络在板料弯曲回弹预测中的应用

回弹是板料冲压成形中影响工件质量的重要因素，因为它是一个多变量相互作用的高度非线性问题，至今在解析和数值方法中未能找到一个很有效的解决途径。该文提出利用自适应模糊神经网络(ANFIS)对非线性问题的良好逼近能力，采用基于有限元方法获得训练样本，经训练后得到具有回弹预测能力的ANFIS模型。实验验证了该方法的有效性。     

A performance index for topology and shape optimization of plate bending problems with displacement constraints

This paper presents a performance index for topology and shape optimization of plate bending problems with displacement constraints. The performance index is developed based on the scaling design approach. This performance index is used in the Performance-Based Optimization (PBO) method for plates in bending to keep track of the performance history when inefficient material is gradually removed from the design and to identify optimal topologies and shapes from the optimization process. Several examples are provided to illustrate the validity and effectiveness of the proposed performance index for topology and shape optimization of bending plates with single and multiple displacement constraints under various loading conditions. The topology optimization and shape optimization are undertaken for the same plate in bending, and the results are evaluated by using the performance index. The proposed performance index is also employed to compare the efficiency of topologies and shapes produced by different optimization methods. It is demonstrated that the performance index developed is an effective indicator of material efficiency for bending plates. From the manufacturing and efficient point of view, the shape optimization technique is recommended for the optimization of plates in bending. Received November 27, 1998?Revised version received June 6, 1999     

基于JSTAMP/NV的汽车横梁回弹分析

为测试JSTAMP／NV的回弹仿真精度,以2005年国际板材成型数值模拟会议（Numisheet’2005）提出的预测汽车横梁回弹的基准考题为例,采用Y—u材料模型,基于JSTAMP／NV仿真冲压拉深成型和回弹的过程．仿真结果与试验结果吻合良好,表明利用JSTAMP／NV能有效预测汽车横梁的回弹．     

管道弯制CAD/CAM系统的设计与实现

对管道弯制涉及的问题进行了分析,描述了管道弯制CAD/CAM系统整体框架,提出系统模块划分方案;给出了由管道XYZ坐标到YBC坐标的转换算法,结合管道回弹和延伸特性,建立了回弹延伸补偿算法,对弯管数据进行了修正补偿,并生成精确下料尺寸;根据工艺条件和碰撞因素,分别从可弯制性初步分析和仿真分析两个层次对管道的可弯制性进行了分析;利用Visual C 编程工具和OpenGL图形库对系统进行了实现.目前系统已成功投入运行.     

Application of an interface failure model to predict fatigue crack growth in an implanted metallic femoral stem

A novel computational modelling technique has been developed for the prediction of crack growth in load bearing orthopaedic alloys subjected to fatigue loading. Elastic-plastic fracture mechanics has been used to define a three-dimensional fracture model, which explicitly models the opening, sliding and tearing process. This model consists of 3D nonlinear spring elements implemented in conjunction with a brittle material failure function, which is defined by the fracture energy for each nonlinear spring element. Thus, the fracture energy criterion is implicit in the brittle material failure function to search for crack initiation and crack development automatically. A degradation function is employed to reduce interfacial fracture properties corresponding to the number of cycles; thus fatigue lifetime can be predicted. Unlike other failure modelling methods, this model predicts the failure load, crack path and residual stiffness directly without assuming any pre-flaw condition. As an example, fatigue of a cobalt based alloy (CoCrMo) femoral stem is simulated. Experimental fatigue data was obtained from four point bending tests. The finite element model simulated a fully embedded implant with a constant point load. Comparison between the model and mechanical test results showed good agreement in fatigue crack growth rate.