An optimization method for radial forging process using ANN and Taguchi method

In this study, the artificial neural network (ANN) and the Taguchi method are employed to optimize the radial force and strain inhomogeneity in radial forging process. The finite element analysis of the process verified by the microhardness test (to confirm the predicted strain distribution) and the experimental forging load published by the previous researcher are used to predict the strain distribution in the final product and the radial force. At first, a combination of process parameters are selected by orthogonal array for numerical experimenting by Taguchi method and then simulated by FEM. Then the optimum conditions are predicted via the Taguchi method. After that, by using the FEM results, an ANN model was trained and the optimum conditions are predicted by means of ANN (using genetic algorithm as global optimization procedure) and compared with those achieved by the Taguchi method. The optimum conditions are verified by FEM, and good agreement is found between the two sets of results.     

Multi-objective optimization of forming parameters for tube hydroforming process based on the Taguchi method

Tube hydroforming is an attractive manufacturing technology which is now widely used in many industries, especially the automobile industry. The purpose of this study is to develop a method to analyze the effects of the forming parameters on the quality of part formability and determine the optimal combination of the forming parameters for the process. The effects of the forming parameters on the tube hydroforming process are studied by finite element analysis and the Taguchi method. The Taguchi method is applied to design an orthogonal experimental array, and the virtual experiments are analyzed by the use of the finite element method (FEM). The predicted results are then analyzed by the use of the Taguchi method from which the effect of each parameter on the hydroformed tube is given. In this work, a free bulging tube hydroforming process is employed to find the optimal forming parameters combination for the highest bulge ratio and the lowest thinning ratio. A multi-objective optimization approach is proposed by simultaneously maximizing the bulge ratio and minimizing the thinning ratio. The optimization problem is solved by using a goal attainment method. An example is given to illustrate the practicality of this approach and ease of use by the designers and process engineers.     

Multi-objective optimization of injection molding process parameters in two stages for multiple quality characteristics and energy efficiency using Taguchi method and NSGA-II

In this paper, the parameters optimization of plastic injection molding (PIM) process was obtained in systematic optimization methodologies by two stages. In the first stage, the parameters, such as melt temperature, injection velocity, packing pressure, packing time, and cooling time, were selected by simulation method in widely range. The simulation experiment was performed under Taguchi method, and the quality characteristics (product length and warpage) of PIM process were obtained by the computer aided engineering (CAE) method. Then, the Taguchi method was utilized for the simulation experiments and data analysis, followed by the S/N ratio method and ANOVA, which were used to identify the most significant process parameters for the initial optimal combinations. Therefore, the range of these parameters can be narrowed for the second stage by this analysis. The Taguchi orthogonal array table was also arranged in the second stage. And, the Taguchi method was utilized for the experiments and data analysis. The experimental data formed the basis for the RSM analysis via the multi regression models and combined with NSGS-II to determine the optimal process parameter combinations in compliance with multi-objective product quality characteristics and energy efficiency. The confirmation results show that the proposed model not only enhances the stability in the injection molding process, including the quality in product length deviation, but also reduces the product weight and energy consuming in the PIM process. It is an emerging trend that the multi-objective optimization of product length deviation and warpage, product weight, and energy efficiency should be emphasized for green manufacturing.     

智能注射成形中工艺参数的多目标自学习优化

注射成形工艺参数是保障产品质量的关键因素。传统试错法严重依赖工艺人员的试模经验,随着注射成形工艺广泛应用于电子、航空航天等国家战略领域,产品的高端化对工艺参数智能化设置水平提出更高的要求。由于成形产品存在多方面的质量要求,且不同质量指标间可能相互制约,因此亟需一种工艺参数多目标智能优化方法,以获得不同优化目标间的帕累托最优。已有学者利用智能优化方法,如非支配排序遗传算法等,对多目标优化问题进行求解,但是此类方法需大量样本数据对质量-参数关系进行建模,存在试验次数多、且对不同材料及模具的适应性较差等问题。为解决上述问题,提出一种注射成形工艺参数多目标自学习优化方法,在优化过程中实时计算并更新各个工艺参数的梯度,并由不同质量指标的多梯度下降算法对多个目标函数进行优化,在优化过程中实现各工艺参数对产品质量影响程度的自主学习,省去了采集大量数据来建立多个质量模型的过程,实现了注射成形工艺参数的高效智能优化。在基准测试函数实验中,所提方法的优化结果与理论解的相对误差小于2%。同时数值仿真与注射成形实验结果表明,所提方法能高效获得多个优化目标的帕累托最优。     

Optimization of machining parameters in rotary EDM process by using the Taguchi method

Electrical discharge machining (EDM) is one of the advanced methods of machining. Most publications on the EDM process are directed towards non-rotational tools. But rotation of the tool provides a good flushing in the machining zone. In this study, the optimal setting of the process parameters on rotary EDM was determined. A total of three variables of peak current, pulse on time, and rotational speed of the tool with three types of electrode were considered as machining parameters. Then some experiments have been performed by using Taguchi's method to evaluate the effects of input parameters on material removal rate, electrode wear rate, surface roughness, and overcut. Moreover, the optimal setting of the parameters was determined through experiments planned, conducted, and analyzed using the Taguchi method. Results indicate that the model has an acceptable performance to optimize the rotary EDM process.     

Optimization of green sand casting process parameters by using Taguchi’s method

This paper analyses various significant process parameters of the green sand casting process. An attempt has been made to obtain optimal settings of the green sand casting process in order to yield the optimum quality characteristics of the spheroidal graphite (SG) cast iron rigid coupling castings. The process parameters considered are: green strength, moisture content, permeability and mould hardness. The effect of selected process parameters and its levels on the casting defects and the subsequent optimal settings of the parameters have been accomplished using Taguchi’s parameter design approach. The result indicates that the selected process parameters significantly affect the casting defects of SG cast iron rigid coupling castings. The estimation of the optimum performance characteristics of green sand casting at the optimum levels of parameters is done in this paper and the results are verified by confirming with practical experiments.     

A study on precision forging of spur gear forms and spline by the upper bound method

Precision forging is an important manufacturing procedure of spline and spur gear forms. It has advantages of improved strength, good tolerance, saving billet material, dispensing with the cutting, etc. In this paper, a mathematical model using an upper bound method is proposed for forging of spur gear forms and spline to investigate the plastic deformation behavior of billet within the die cavity. The material of solid billet was assumed as rigid–plastic and the shape of the tooth profile was accounted for the mathematical modeling of the kinematically admissible velocity field assumed for the plastic zone. The non-uniform velocity was employed for simulating the inhomogeneous deformation and the effect of barreling during the forging. Using the present model, various effects of forming parameter such as the friction factor, reduction, number of teeth, etc. upon the non-dimensional forging pressure, forging force and barreling of the spur gear forms and spline were analyzed systematically and the results compared with those of other researcher's analytical and experimental work. It is shown that the present modeling of the process improves knowledge of the process design performance for the precision forging of spur gear form and spline.     

基于MATLAB的斜齿轮传动多目标可靠性优化设计

介绍了齿轮传动的多目标设计方法,以斜齿轮体积和传动平稳可靠性为目标函数,在保证齿轮强度可靠性的前提下,建立了斜齿圆柱齿轮传动的多目标优化设计数学模型.并且结合实例利用科学计算软件MATLAB的优化工具箱求解优化问题.目前,对于斜齿轮优化设计的研究主要集中在减小体积方面,一般不考虑传动平稳性.对减小体积和提高传动平稳可靠性两个目标进行了联合优化,这对于齿轮传动设计具有理论指导意义.     

Design and manufacturing of a straight bevel gear in hot precision forging process using finite volume method and CAD/CAE technology

Forging simulation offers significant cost and time advantages by providing detailed insight into the forging process before tool selection and process decisions are made on the shop floor. Process data such as material flow, stresses, strains and temperature are readily accessible to a user at any point throughout the simulation process, as well as at any location within the forged part. Potential defects such as laps and under-fill of die cavities can be easily identified and corrected before part production begins. In addition, the influence of the process conditions such as lubrication and pre-form can be easily quantified and assessed. In the present work, hot precision forging process of the straight bevel gear is simulated numerically using finite volume method and computer-aided design/computer-aided engineering technology. The required force for the forging process, as well as the final shape of the bevel gear, is determined through numerical estimation. The simulation results are confirmed through the comparison with the experimental data available in DIN standards. Finally, the pre-form dies, the final die, and the bevel gear are manufactured. It is concluded that this method can be effectively used to optimize the forging process to maximize the mechanical strength, minimize material scrap, and hence reduce the overall cost of manufacture.     

齿轮毛坯锻造成形内部质量控制与工艺优化设计

提出了一种基于简约下降梯度法的锻造成形工艺优化方法,采用有限元数值模拟技术与优化技术相接合的方法优化变形工艺使得工件内部损伤值最小.采用镀件所有单元的最大损伤值为衡量锻件变形损伤的指标,以零件毛坯的初始高径比为设计变量,建立了优化设计的数学模型.对齿轮毛坯非等温热锻成形工艺参数进行优化取得了良好的效果.     

高速精密数控车床床鞍结构参数多目标优化

为了实现机床关键部件的多目标优化设计,以一种高速精密数控车床的床鞍为研究对象,采用灵敏度分析和试验分析方法,研究床鞍结构参数对床鞍动态特性的影响规律;以床鞍的前两阶固有频率和质量为优化目标,以导轨悬伸长度、导轨跨距和滑块间距为设计变量,建立多目标优化方程;运用粒子群算法和模糊综合评判法得到最优解。优化后,床鞍的一阶固有频率提高33%,二阶固有频率提高4.13%,床鞍质量减轻7.76%。优化结果表明所提优化方法是可行的,为床鞍的优化设计提供了理论依据。     

Roughness optimization of flow-formed tubes using the Taguchi method

The present study reports the effect of various flow-forming process parameters and roller geometry on the roughness of flow-formed tubes of commercial pure copper UNS C11000. Thickness reduction ratio, feed rate, angular speed of mandrel, attack angle of roller, roller tip radius, and smooth angle of roller were considered as variable parameters. The effects of these input parameters on the roughness have been critically analyzed using the Taguchi method. Through ANOVA analysis, it has been found that the roller tip radius is the most important parameter affecting roughness followed by thickness reduction ratio. Selection of an optimum combination of variable parameters was performed based on “average of results.” The minimum roughness of 1.37 μm was achieved when the process parameters were set at their optimum values.     

二级斜齿圆柱齿轮减速器的多目标优化设计

通过对二级斜齿圆柱齿轮减速器系统的传动情况设计了一套优化方案,建立了多目标优化方法,根据应用值得实际参数确定了约束条件,对系统进行了优化,对该齿轮传动系统在设计上提供了较新的解决办法。     

Tolerance design of robot parameters using Taguchi method

A robotic arm must be able to manipulate objects with high accuracy and repeatability. As with every physical system, there are number of noise factors cause uncertainty in the performance. A probabilistic approach has been used to model, the otherwise difficult to model, noise effects. This paper presents the approach utilised in selection of tolerance specification of robot kinematic and dynamic parameters using experimental design technique for reduction of performance variations. The concept of inner and outer orthogonal arrays proposed by Taguchi is employed to identify the significant parameters and select the optimal tolerance range. The performance measure, i.e. signal-to-noise ratio is utilised to validate by Monte Carlo simulations and to complement above study individual parameter tolerance sensitivity are investigated. To provide insight to investigation, parameter sensitivity maps are plotted. The tolerance specification selection methodology of a manipulator is illustrated by taking 2-DOF RR planar manipulator with payload.     

Optimization of squeeze casting process parameters using Taguchi analysis

Squeeze casting is a hybrid metal forming process combining features of both casting and forging in one operation. This paper reports a research in which an attempt was made to prepare solid cylindrical components of LM24 aluminum alloy through squeeze casting. The primary objective was to investigate the effect of process parameters on the mechanical properties exhibited by the castings produced though squeeze casting process. A set of trials were conducted based on parameters settings suggested in Taguchi’s offline quality control concept. The experimental results indicate that the squeeze pressure and the die-preheating temperature were the parameters making significant contribution toward improvement in mechanical properties of squeeze cast LM24 aluminum alloy.     

Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method

Wire electrical discharge machining (WEDM) is extensively used in machining of conductive materials when precision is of prime importance. Rough cutting operation in WEDM is treated as a challenging one because improvement of more than one machining performance measures viz. metal removal rate (MRR), surface finish (SF) and cutting width (kerf) are sought to obtain a precision work. Using Taguchi’s parameter design, significant machining parameters affecting the performance measures are identified as discharge current, pulse duration, pulse frequency, wire speed, wire tension, and dielectric flow. It has been observed that a combination of factors for optimization of each performance measure is different. In this study, the relationship between control factors and responses like MRR, SF and kerf are established by means of nonlinear regression analysis, resulting in a valid mathematical model. Finally, genetic algorithm, a popular evolutionary approach, is employed to optimize the wire electrical discharge machining process with multiple objectives. The study demonstrates that the WEDM process parameters can be adjusted to achieve better metal removal rate, surface finish and cutting width simultaneously.     

Surface roughness optimization of cold-sprayed coatings using Taguchi method

In this paper, Taguchi L 18 orthogonal array have been employed for depositing the electro-conductive coatings by varying various process parameters, i.e., substrate material, type of powder feeding arrangement, stagnation gas temperature, stagnation gas pressure, and stand-off distance. The response parameter of the coatings so produced is measured in terms of surface roughness. The optimum process parameters are predicted on the basis of analyses (ANOVA) of the raw data and signal to noise ratio. The significant process parameters in order of their decreasing percentage contribution are: stagnation pressure, stand-off distance, substrate material, stagnation temperature of the carrier gas, and feed arrangement of the powder particles, respectively.