Multiple-response optimization for micro-endmilling process using response surface methodology

In the present trend, new fabrication methods for producing miniaturized components are gaining popularity due to the recent advancements in micro-electro mechanical systems. Micro-machining differs from the traditional machining with the small size tool, resolution of x?Cy and z stages. This paper focuses RSM for the multiple response optimization in micro-endmilling operation to achieve maximum metal removal rate (MRR) and minimum surface roughness. In this work, second-order quadratic models were developed for MRR and surface roughness, considering the spindle speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models were used for multiple-response optimization by desirability function approach to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in good agreement with the predicted values.     

Multi-response optimization of process parameters based on response surface methodology for pure titanium using WEDM process

This paper presents an investigation on WEDM of pure titanium (grade-2). An attempt has been made to model the four response variables, i.e., machining rate, surface roughness, dimensional deviation and wire wear ratio in WEDM process using response surface methodology. The experimental plan is based on Box–Behnken design. The six parameters, i.e., pulse on time, pulse off time, peak current, spark gap voltage, wire feed and wire tension have been varied to investigate their effect on output responses. These responses have been optimized using multiresponse optimization through desirability. The ANOVA has been applied to identify the significance of developed model. The test results confirm the validity and adequacy of the developed RSM model. Finally, the optimum parametric setting has been designed for the optimization of process.     

基于ANSYS/LS-DYNA的受控喷丸工艺过程仿真

将喷丸过程简化为丸粒撞击工件的模型,丸粒看作刚性体,运用ANSYS/LS-DYNA软件进行了数值模拟,分析了覆盖率对残余压应力分布的影响,得出在不完整喷丸覆盖率下工件表面会产生残余拉应力.在单个丸粒模型中,将丸粒的材料改为塑性硬化材料,分析丸粒的速度对残余压应力分布的影响,得出丸粒的材料参数一定时,存在最优喷丸速度,丸速过高会导致丸粒的变形能增加,而使工件表层的最大压应力值和应力层深度下降.     

Application of Six-Sigma DMAIC methodology to sand-casting process with response surface methodology

This paper deals with the application of Six-Sigma methodology to the flywheel casting process in foundry to minimize the defects in this process. The primary tools used in this interventionist process were the process map, cause-and-effect matrix and the failure mode effective analysis. The present study proposes to measure the performance criteria of the process through investigating the effect of working parameters, namely, moisture content, green strength, permeability, and loss on ignition on sand preparation. The experimental results were statistically analyzed and modeled through response surface methodology (RSM). Based on the findings, the optimized process parameters were taken for experiment and better performance obtained in the production process was confirmed. The comparison between the existing process and the proposed process has been attempted in this paper and the results have been discussed in detail.     

Quality chain design and optimization by multiple response surface methodology

To maintain optimal quality characteristics in the defined specification limits is a vital decision for any industry and service system. To avoid nonconformity in outputs, the stream of variations and their potential causes must be identified so that the response variables fall into desirable limits across the manufacturing or service chain. Response surface methodology is considered as a powerful technique to facilitate the analysis of the mentioned problem. This paper presents the general quality chain design problem as a mathematical program and also proposes a method to solve it using multiple response surface methodology. An example of multistage processes is analyzed by the proposed approach to show its efficacies numerically and analytically.     

Energy saturation of metal parts in surface plastic deformation (shot peening)

A new algorithm simulating the change in surface plastic deformation during shot peening is described. Using this algorithm, metallic panels with specified curvature may be produced.     

Modeling and optimization of a reluctance accelerator using DOE-based response surface methodology

This paper introduces experiment-based modeling and optimization of a reduced-scale Electromagnetic launcher (EML) using the Design of experiments (DOE) technique. Response surface models describing the velocity and kinetic energy of the launched projectile were developed using the Box–Behnken method with design variable transforms, and an Analysis of variance (ANOVA) was conducted to refine the models by removing statistically insignificant terms. A bi-objective optimization problem with the maximum velocity and maximum kinetic energy as objects was considered, and a Pareto front was obtained using the generated response surfaces as the solution of the problem. Verification tests on the optimal design points were conducted to demonstrate the validity of the developed models.

     

Loading path optimization of a hydroformed part using multilevel response surface method

In tube hydroforming, the loading path that is the relationship between axial feeding and internal fluid pressure is of important significance. Researchers have employed various optimization approaches to find an optimum loading path. In this research, a statistical method based on finite element analysis has been developed. An accurate FEA has been used to simulate the process and to find the response of the process to the loading. By performing an experimental test, the model is verified in comparison with the actual T part. The multilevel response surface method (MLRSM) has been used to model the responses from the finite element analysis. The behavior of the process can be predicted using the response surface methodology (RSM) model, and then, the obtained model is used to optimize the process. The optimum point in the RSM highly depends on the initial range of design variables. Thus, after finding the optimum point in each level, the ranges of variables are adjusted around the last optimum point. Then, the optimization process can be continued as a multilevel process. In the performed optimizations, the thickness variance has been considered as the objective function and the protrusion height as the constraint. The thickness variation based on the optimum loading path is highly improved, and it shows that multilevel RSM is very effective in improving the results.     

Analysis of shrinkage and warpage in an injection-molded part with a thin shell feature using the response surface methodology

This paper presents a systematic methodology to analyze the shrinkage and warpage in an injection-molded part with a thin shell feature during the injection molding process. The systematic experimental design based on the response surface methodology (RSM) is applied to identify the effects of machining parameters on the performance of shrinkage and warpage. The experiment plan adopts the centered central composite design (CCD). The quadratic model of RSM associated sequential approximation optimization (SAO) method is used to find the optimum value of machining parameters. One real case study in the injection molding process of polycarbonate/acrylonitrile butadiene styrene (PC/ABS) cell phone shell has been performed to verify the proposed optimum procedure. The mold temperature (M _T), packing time (P _t), packing pressure (P _P) and cooling time (C _t) in the packing stage are considered as machining parameters. The results of analysis of variance (ANOVA) and conducting confirmation experiments demonstrate that the quadratic models of the shrinkage and warpage are fairly well fitted with the experimental values. The individual influences of all machining parameters on the shrinkage and warpage have been analyzed and predicted by the obtained mathematical models. For the manufacture of PC/ABS cell phone shell, the values of shrinkage and warpage present the reduction of 37.8 and 53.9%, respectively, using this optimal procedure.     

Parametric optimization of ultrasonic metal welding using response surface methodology and genetic algorithm

This paper focuses on the development of an effective methodology to determine the optimum welding conditions that maximize the strength of joints produced by ultrasonic welding using response surface methodology (RSM) coupled with genetic algorithm (GA). RSM is utilized to create an efficient analytical model for welding strength in terms of welding parameters namely pressure, weld time, and amplitude. Experiments were conducted as per central composite design of experiments for spot and seam welding of 0.3- and 0.4-mm-thick Al specimens. An effective second-order response surface model is developed utilizing experimental measurements. Response surface model is further interfaced with GA to optimize the welding conditions for desired weld strength. Optimum welding conditions produced from GA are verified with experimental results and are found to be in good agreement.     

Influence of shot peening on the surface durability of thermomechanically treated En 24 steel spur gears

En steel, in untreated and thermal treated conditions, with and without shot peening, were tested in a back-to-back gear test rig. Their contact fatigue characteristics were studied and S–N curves have been established. Contact fatigue strength of shot peened gears for a given life showed an improvement in relation to unpeened gears.     

Impact of surface hardening treatment generated by shot peening on the fatigue life of brass alloy

Brass alloy is widely used because of some attractive properties such as high electrical and thermal conductivity. But its fatigue performance after surface treatment is not very well explored in literature. Thus, in the present work, particular emphasis was given to the influence of surface treatment by shot peening on the fatigue life of brass alloy, throughout surface roughness and microstructural evolution. Fatigue tests were performed on unpeened, peened and peened then polished specimens. Various times of surface hardening treatment as 30, 60 and 120 min were considered. Experimental results reveal that the fatigue life of peened brass alloy decrease for all studied hardening treatment conditions. Surface roughness and microstructural properties showed large sensitivity to the shot peening process of brass alloy.     

A study of optimization of injection molding process parameters for SGF and PTFE reinforced PC composites using neural network and response surface methodology

This study analyzed variations of mechanical characteristics that depend on the injection molding techniques during the blending of short glass fiber and polytetrafluoroethylene reinforced polycarbonate composites. A hybrid method including back-propagation neural network (BPNN), genetic algorithm (GA), and response surface methodology (RSM) are proposed to determine an optimal parameter setting of the injection molding process. The specimens are prepared under different injection molding processing conditions based on a Taguchi orthogonal array table. The results of 18 experimental runs were utilized to train the BPNN predicting ultimate strength, flexural strength, and impact resistance. Simultaneously, the RSM and GA approaches were individually applied to search for an optimal setting. In addition, the analysis of variance was implemented to identify significant factors for the injection molding process parameters and the result of BPNN integrating GA was also compared with RSM approach. The results show that the RSM and BPNN/GA methods are both effective tools for the optimization of injection molding process parameters.     

基于中心点精确响应面法的板壳结构优化

对响应面方法中两个最为关键的概念——近似函数及试验设计做了简单描述,选择线性函数作为约束条件的近似函数形式,并对位移和应力约束作不同处理,位移约束不合常数项,而应力约束含常数项。提出了一种适合建立一阶形式响应面并使结构分析次数最少的试验设计方法——中心扩展法。求解响应面时在最小二乘法的基础之上作了改进,提出中心点精确响应面法,使拟合的响应面中心点处的响应值精确等于有限元分析值。最后通过数值算例说明改进后的响应面法对于板壳结构优化的可行性和优越性。     

Aerodynamic design optimization for a canopy based on response surface methodology and a multi-objective genetic algorithm

In the present study, the aerodynamic performance and flight stability of a two-dimensional (2D) canopy in a paraglider are optimized using a combination of response surface methodology (RSM) and a multi-objective genetic algorithm (MOGA) coupled with the unsteady Reynolds-averaged Navier-Stokes (URANS) equations solver. Compared to a 2D base case, an optimized canopy, featured by reduced airfoil thickness, shows an increase in the aerodynamic performance up to 18.9 % based on lift-to-drag ratio, while the flight stability is similar between them. An optimized three-dimensional (3D) canopy is constructed by duplicating the 2D canopy along the arc direction to identify the effects of the optimization on an actual 3D canopy. Based on large-eddy simulation (LES) data of the optimized 3D canopy and base 3D canopy, we show an improvement of the aerodynamic performance and stability of the optimized 3D canopy, consistent with our results from the 2D canopies.