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.     

Computer-aided engineering for sheet metal forming: definition of a springback quality function

Computer-aided engineering methods are extensively applied to sheet metal forming integrated design. The adoption of a new class of materials, the advanced high strength steels, has increased the occurrence of springback, and consequently the request for tools oriented to springback reduction and optimization. This paper presents an approximated formulation to compute the springback field after stamping through the finite element analysis of the process. This can be found assuming that the residual field of nodal forces after stamping produces a springback shape referable to a linear combination of n modes of vibration of the nominal shape of the component. The aim of this formulation is not that of substituting the finite element analysis of the springback but rather to make use of the coefficients of the linear combination, so to define a global quality function for springback. In this way, Robust Design methods or other current optimization procedures to improve the stamping process as for structural defects (such wrinkling, necking and flatness) can be applied also for the reduction of springback. The meaning of these coefficients will be shown through three test cases and the consistency of the formulation will be discussed according to the number of modes of vibration included in the computation.     

响应面法优化波纹巴非蛤酶解工艺的参数

应用响应面分析法分别优化波纹巴非蛤蛋白2段酶解的条件,第一段酶解使用胰蛋白酶,以蛋白质利用率为响应值;第二段酶解用木瓜蛋白酶,以肽得率为响应值.最终确定第一段酶解的最优条件为:酶与底物质量比为0.4:100,酶解时间为3h,酶解温度为52.0℃;第二段酶解的最优条件为:酶与底物的质量比为0.25:100,酶解时间为7.62 h,酶解温度为57.0℃,在此条件下,肽得率为54.35％,与模型的预测值55.67％接近.经2段酶解的上清液中小分子肽平均含量为2.25％.     

Auto-tuning and adaptive control of sheet metal forming

This paper describes the design and implementation of automatic controller tuning and model reference adaptive control (MRAC) to improve part quality in stamping and extends previous work on a manually-tuned fixed-gain process controller. Automatic tuning is described with a discussion of implementation issues in the presence of plant disturbances. Design of a direct MRAC, whose controller gains are continuously adjusted to accommodate changes in process dynamics and disturbances, is investigated, including simulation-based robustness analysis of the adaptation law and a consideration of constrained estimation in the recursive least squares algorithm to address practical implementation issues. The performance of the MRAC process controller designed through simulation is experimentally validated. Good tracking of the reference process variable (i.e., punch force), and significant part quality improvement in the presence of disturbances, is achieved.     

响应面分析法优化水提取甜叶菊苷工艺的研究

为优化水提取甜叶菊苷的工艺,在单因素试验基础上,选择料液比,提取温度,提取时间为自变量,甜叶菊苷提取率为响应值,利用Box-Benhnken中心组合试验和响应面分析法,研究各自变量交互作用及其对甜叶菊苷提取率的影响,模拟得到二次多项式回归方程的预测模型,并确定水提取甜叶菊工艺最佳条件为:选取料液比为1:26,提取温度为72℃,提取时间为118 min.在此优化条件下提取率达到21.02%。     

Response surface methodology for constrained simulation optimization: An overview

This article summarizes ‘generalized response surface methodology’ (GRSM), extending Box and Wilson’s ‘response surface methodology’ (RSM). GRSM allows multiple random responses, selecting one response as goal and the other responses as constrained variables. Both GRSM and RSM estimate local gradients to search for the optimum. These gradients are based on local first-order polynomial approximations. GRSM combines these gradients with Mathematical Programming findings to estimate a better search direction than the steepest ascent direction used by RSM. Moreover, these gradients are used in a bootstrap procedure for testing whether the estimated solution is indeed optimal. The focus of this paper is the optimization of simulated (not real) systems.     

磁致位移传感器在板材成型控制系统中的应用

介绍了磁致伸缩线性位移传感器的原理及使用方法,给出了该传感器在板材成型控制系统中的应用实例,并对系统的静态特性及系统控制精度进行了分析与评价.对测试系统进行标定,其相关系数为0.9999,回程误差为0.2880V,满量程电压为7.0154V,滞后优于4%FS,分辨力达0.002%FS,灵敏度达65.3mV/mm,控制信号的滞后误差最大为0.33mm.     

A methodology of forming manufacturing cells using manufacturing and design attributes

This study develops a methodology for forming machine cells using part's design and manufacturing dissimilarities. The proposed methodology is divided into two sequential phases. In phase I parts are grouped into families based upon their design and manufacturing attributes. In phase II, the machines are grouped into manufacturing cells based on relevant operational costs and the various cells are assigned part families using an optimization technique.     

Robust design of sheet metal forming process based on adaptive importance sampling

Optimization methods have been widely applied in sheet metal forming area. However, the existence of variations during manufacturing processes significantly may influence final product quality, rendering non-robust optimal solutions. In this paper, experiments were conducted to investigate how a stochastic behavior of noise factors affected stamping quality. Robust design models for sheet metal forming process integrated adaptive importance sampling with response surface method, in order to minimize impact of the variations and achieve reliable process parameters. Support Vector Machine with nonlinear capability in both pattern recognition and regression was adopted to map the relation between input process parameters and part quality. A cup drawing example was employed to verify the feasibility of the proposed method. Comparisons were conducted between different optimization models to demonstrate robustness of the adaptive importance sampling method. Final results showed that the stamping part quality was optimized under the specified constraint requirements.     

响应曲面分析法对青藤碱超临界CO2流体萃取条件的优化

以青风藤药材为原料,在单因素实验研究的基础上,采用Box-Behnken响应曲面分析法对影响青风藤药材中青藤碱超临界CO2萃取得率的关键因素:萃取时间、压力、温度进行了优化,旨在为青藤碱新型、绿色提取分离方法作探讨.根据统计模型进行了工艺参数的优选,以得率为指标,优化后所得青藤碱超临界CO2萃取工艺条件为:萃取压力为27.63 MPa,萃取温度为50.68℃,萃取时间为120.24 mim.该条件下得率为1.372%.验证试验证实了该方程的预测值与试验值之间具有较好的拟合度.     

Parallel boundary and best neighbor searching sampling algorithm for drawbead design optimization in sheet metal forming

In the present paper, a Kriging-based metamodeling technique is used to minimize the risk of failure in a sheet metal forming process. The Kriging-based models are fitted to data that are obtained for larger experimental areas than the areas used in low-order polynomial regression metamodels. Therefore, computational time and memory requirement can be an obstacle for Kriging for data sets with many observations. To improve the usability of the Kriging-based metamodeling techniques, a parallel intelligent sampling approach: boundary and best neighbor searching (BBNS) (Wang et al., J Mater Process Technol 197(1–3):77–88, 2008a) is suggested. Compared with the serial BBNS version, the sampling procedure is performed synchronously. Thus, larger sample size should be considered for real-life problems when multiple processors are available. Furthermore, the parallel strategy is prone to converge based on more samples. The performance of the parallel approached is verified by means of nonlinear test functions. Moreover, the drawbead design in sheet metal forming is successfully optimized by the parallel BBNS approach and Kriging metamodeling technique. The optimization results demonstrate that the parallel BBNS approach improves the applicability of the Kriging metamodeling technique substantially.     

A design methodology for structural and control systems of a prosthetic leg

A design methodology is proposed to optimize a prosthetic leg considering the structural and control aspects. Previous studies mainly focused on each of a structural design problem or a control problem. The structural design variables of a prosthetic leg are determined in a structural design problem while the trajectory tracking based on the human gait cycle is found to be a control problem. The two problems have been separately solved. However, they should be simultaneously considered to obtain a better design. Then the problem would be nonlinear dynamic response optimization of structural and control systems. An optimization method was recently developed for a linear system of structural and control design problems using the equivalent static loads (ESLs). In this study, a design methodology for the prosthetic leg is presented by expanding the equivalent static loads method (ESLM) to nonlinear dynamic systems. A simple example is solved to validate the proposed methodology, and then a prosthetic leg is optimized to reduce the weight and energy consumption.     

Tool path programming optimization for incremental sheet forming applications

Incremental sheet forming is an emerging process to manufacture sheet metal parts that is well adapted for small batch production or prototypes. The adjustment time is short, as it is sufficient to modify the tool motions to optimize the manufacturing process. Tool path generation therefore becomes a key topic linked to incremental sheet forming, and process characteristics ask for dedicated tool paths. Hence, this paper first discusses the impact of tool path types and other programming parameters on process implementation through an experimental campaign performed on a parallel kinematics machine tool. Then, a new approach to generate and control Intelligent CAM programmed tool paths is proposed. The major purpose of this innovative concept is to use process constraints for programming and controlling the tool path, which are adapted during the running of the CNC program according to real-time process data evaluation. Validation studies and an industrial implementation are finally presented to assess the efficiency of the proposed approach.     

Design optimization by response surface methodology: application to crashworthiness design of vehicle structures

Standards imposed by certification regulations are very strict and the requirements of the customer in terms of vehicle safety are always increasing. It is often necessary to redesign several vehicle components in order to achieve a global better performance. Design optimization by response surface methodology has been effectively used to improve the mechanical behaviour of several automotive components in impact load conditions. An iterative optimization algorithm based on a multipoint approximation scheme and on the steepest descent method has been used to identify the best geometrical configuration of several energy absorbing devices. Load uniformity parameter LU defined as the ratio between the maximum and the mean crushing forces has been used as objective function. Three design cases have been analysed and the results of the optimization process are shown.     

A design methodology for switched discrete time linear systems with applications to automotive roll dynamics control

In this paper we consider the asymptotic stability of a class of discrete-time switching linear systems, where each of the constituent subsystems is Schur stable. We first present an example to motivate our study, which illustrates that the bilinear transform does not preserve the stability of a class of switched linear systems. Consequently, continuous time stability results cannot be transformed to discrete time analogs using this transformation. We then present a subclass of discrete-time switching systems that arise frequently in practical applications. We prove that global attractivity for this subclass can be obtained without requiring the existence of a common quadratic Lyapunov function (CQLF). Using this result, we present a synthesis procedure to construct switching stabilizing controllers for an automotive control problem, which is related to the stabilization of a vehicle’s roll dynamics subject to switches in the center of gravitys (CG) height.     

The parameters optimisation design for variable speed control momentum gyroscopes

Control momentum gyroscopes (CMGs) have many advantages over other actuators for the attitude control of a spacecraft. Compared with the single-gimbal control moment gyroscopes (SGCMGs), the mass and power of the flywheel of variable-speed control moment gyroscopes (VSCMGs) are greatly increased. In this paper, a new solving strategy of singularity problem is proposed, which concludes the exchangeable momentum and steering law, and the parameters of VSCMGs are designed based on the constraint of singular problem. The configuration characteristics of VSCMGs with the constraint of upper and lower bounds of the flywheel regulation speed are revealed. The steering characteristics of weighted pseudo-inverse with null motion (WPINM) are analysed, then the flywheel torque requirement of WPINM is evaluated based on the geometry theory. At last, the parameter design problem of VSCMGs is cast as multi-objectives and bi-level programming problem. The bi-level programming is transformed into a single-level programming problem by using of the Karush–Kuhn–Tucker condition. Finally, the intelligent algorithm of particle swarm optimisation is presented to solve the nonlinear multi-objective problem.