数据污染下的稳健设计及最优参数的置信区间估计

传统的稳健设计一般假定试验数据为正态分布且无污染,然而在实践中,由于缺乏足够的试验数据以及数据中存在污染等因素,导致用传统的点估计方法无法准确获得某设计点下真实过程的输出值。因此,提出了基于bootstrap重抽样技术估计数据污染下最优参数置信区间的稳健设计方法。首先,采用Hodges-Lehman估计量和Shamos估计量分别估计位置参数和尺度参数;其次,构建过程均值和方差双响应曲面模型,实现稳健设计;然后,利用分位数bootstrapping (Percentile Bootstrapping,PB)、偏差校正分位数bootstrapping (Bias-Corrected Percentile Bootstrapping,BCPB)和偏差校正及加速分位数bootstrapping (Bias-Corrected and accelerated Percentile Bootstrapping,BCaPB)方法分别估计最优参数的bootstrap置信区间;最后,引入欧式距离和广义方差分别度量不同置信区间抵抗污染值的稳健性。通过仿真表明,在解决数据污染的稳健设计中BCPB和BCaPB方法估计的精确度明显高于PB方法,同时BCaPB方法在抵抗污染值干扰方面优于BCPB方法。     

基于双响应面法的公差设计研究

探讨了产品综合成本的构成,以此为基础提出了以产品综合成本最低为目标的公差稳健设计模型,并利用双响应面法(Response Surface Methodology ,RSM) 来实现公差的稳健优化设计。     

基于GPR的3D打印稳健性参数设计

为提高3D打印成型工件精度,降低其对不可控因子变化的敏感性,提出一种基于高斯过程回归建模和改进粒子群寻优的稳健参数设计方法。首先,选择4个显著的可控因子：层厚、打印速度、热床温度、喷嘴温度,并确定其可行域;其次,利用超拉丁方设计获取建模样本集,采用高斯过程回归分别拟合打印工件精度均值和方差的两个响应曲面模型;然后,以均值方差之和最小化为寻优目标,采用惯性权重非线性递减的改进粒子群算法对模型寻优;最后,通过现场实验对寻优结果进行验证。与传统双响应曲面法的对比表明,所提方法在优化结果、拟合性能、寻优能力等方面有显著的改善和提高。     

响应曲面建模的稳健M-回归方法

响应曲面方法是生产过程改进和优化的一种非常有效的方法。在传统的响应曲面模型的建立过程中,通常假定随机误差服从正态分布且相互独立具有相同的方差。但是实际生产中随机误差的方差并不是完全相同,观测值中会存在异常点,这就需要稳健的估计方法来抑制异常点对模型估计的影响。为了降低异常点对响应曲面模型最优值的影响,针对响应曲面方法中的中心复合设计,〖JP2〗充分考虑到不同实验设计位置上可能出现异常点的情况,对稳健M 回归方法：Huber 估计、Tukey 估计和Welsch 估计进行了理论比较研究。研究结果表明Welsch和Tukey 估计能有效改善异常点对响应曲面模型最优值的影响,消弱异常点对中心复合设计的干扰。通过一个来自化工方面的案例,计算了中心复合设计不同位置存在异常点与不存在异常点时,响应曲面模型的最优值,对比分析得出当异常点与响应均值的偏离程度较大时（10倍标准差）,稳健M 估计尤其是Welsch和Tukey 估计显著提高响应曲面建模的稳健性。     

任意分布参数的机械零件的可靠性稳健设计（二）：轴

 应用具有任意分布参数机械零件可靠性稳健设计的理论方法，对具有任意分布参数机械典型轴系零件如半轴、前轴和后桥进行了可靠性稳健设计，给出了计算仿真分析结果，对工程实际的机械零件的可靠性稳健设计提供了理论依据。     

任意分布参数的机械零件的可靠性稳健设计（三）：弹簧

 应用具有任意分布参数机械零件可靠性稳健设计的理论方法，对具有任意分布参数机械典型弹簧系零件如扭杆弹簧和螺旋弹簧，进行了可靠性稳健设计，给出了计算仿真分析结果，对工程实际的机械零件的可靠性稳健设计提供了理论依据．     

考虑测量误差的稳健参数设计北大核心CSSCI

在产品质量设计与制造过程中,通常假定产品或过程的最优参数设计能够准确无误地实施。然而,由于环境温度、湿度以及电压等噪声因素的干扰以及测量误差的作用,过程输入的最优参数设计值往往会呈现出一定的波动,与预定的设计参数值存在一定的偏差。为此,将离线的质量设计技术与在线调整技术相结合,考虑测量误差的情形下,提出一种在线调整的稳健参数设计新方法。首先,通过稳健参数设计方法确定离线控制变量的最优参数设计值;然后,利用传感器技术对生产过程中的可测噪声因子进行在线测量,并借助在线技术调整在线控制变量,对整个过程的期望损失进行调整与补偿,从而降低产品或过程的波动,最终提升产品或过程的设计质量。最后,通过半导体的实际例子验证所提方法的有效性。     

任意分布参数的机械零件的可靠性稳健设计（一）：理论部分

 将可靠性优化设计理论、可靠性灵敏度技术和稳健设计方法相结合，讨论了具有任意分布参数的机械零件的可靠性稳健设计问题，提出了可靠性稳健设计的计算方法．把可靠性灵敏度融入可靠性优化设计模型之中，将可靠性稳健设计归结为满足可靠性要求的多目标优化问题．在基本随机参数的前四阶矩已知的情况下，通过计算机程序可以实现具有任意分布参数的机械零件的可靠性稳健设计，迅速准确地得到具有任意分布参数的机械零件的可靠性稳健设计信息。     

多失效模式机械系统可靠性稳健设计方法研究

将机械系统可靠性设计理论和稳健设计方法相结合,讨论了多失效模式机械系统可靠性稳健设计问题,提出了多失效模式机械系统可靠性稳健设计的计算方法．把可靠性灵敏度融入可靠性优化设计模型之中,将机械系统可靠性稳健设计归结为满足可靠性要求的多目标优化问题．在基本随机参数的前二阶矩已知的情况下,可以迅速准确地得到机械系统可靠性稳健设计信息．     

基于模拟试验法的离散公差稳健设计

 在分析计算机辅助公差设计技术的研究现状的基础上,提出了基于模拟试验法的离散公差稳健设计方法．在该方法中将加工成本与质量损失作为两个独立的目标函数,从而建立离散公差优化设计模型,采用试验设计法和CP方法相结合的技术实现公差的稳健设计,最后用实例证明该方法的可行性．     

Robust Parameter Design: A Review

Parameter design is an engineering methodology intended as a cost‐effective approach for improving the quality of products and processes. The assumption is that there are both controllable factors (control variables) and uncontrollable/difficult to control factors (noise variables) that operate on the quality characteristic of a process. The goal of parameter design is to choose the levels of the control variables that optimize a defined quality characteristic while minimizing the variation imposed on the process via the noise variables. Parameter design was popularized in the mid 1980s by Japanese quality consultant Genichi Taguchi. A panel discussion edited by Nair summarized important responses to Taguchi's ideas and methodology. In the last decade, there have been many applications and new developments in this important area. This review paper focuses largely on the work done since 1992, but a historical perspective of parameter design is also given. Copyright © 2003 John Wiley & Sons, Ltd.     

Studies on the Effects of Estimator Selection in Robust Parameter Design under Asymmetric Conditions

The primary goal of robust parameter design (RPD) is to determine the optimum operating conditions that achieve process performance targets while minimizing variability in the results. To achieve this goal, typical approaches to RPD problems use ordinary least squares methods to obtain response functions for the mean and variance by assuming that the experimental data follow a normal distribution and are relatively free of contaminants or outliers. Consequently, the most common estimators used in the initial tier of estimation are the sample mean and sample variance, as they are very good estimators when these assumptions hold. However, it is often the case that such assumed conditions do not exist in practice; notably, that inherent asymmetry pervades system outputs. If unaccounted for, such conditions can affect results tremendously by causing the quality of the estimates obtained using the sample mean and standard deviation to deteriorate. Focusing on asymmetric conditions, this paper examines several highly efficient estimators as alternatives to the sample mean and standard deviation. We then incorporate these estimators into RPD modeling and optimization approaches to ascertain which estimators tend to yield better solutions when skewness exists. Monte Carlo simulation and numerical studies are used to substantiate and compare the performance of the proposed methods with the traditional approach. Copyright © 2012 John Wiley & Sons, Ltd.     

Ensemble of Surrogates for Dual Response Surface Modeling in Robust Parameter Design

The robust parameter design of industrial processes and products on the basis of the concept of building quality into a design has attracted much attention from researchers and practitioners for many years, and several methods have been studied in the research community. Dual response surface methodology is one of the most commonly used approaches for simultaneously optimizing the mean and the variance of response in quality engineering. Nevertheless, when the relationship between influential input factors and output quality characteristics of a process is very complex (e.g. highly nonlinear and noisy), traditional approaches have their limitations. In this article, we introduced support vector regression, kriging model, and radial basis function, which are commonly used in computer experiments, into robust parameter design, and especially introduced a new strategy that builds the dual response surface using the ensemble of surrogates, which can provide a more robust approximation model. We demonstrated the advantages of kriging, support vector regression, radial basis function, and the ensemble of surrogates by reinvestigating the dual response approach on the basis of parametric, nonparametric, and semiparametric approaches, and a simulation experiment is studied. The results show that our presented models can achieve more desirable results than parametric, nonparametric, and semiparametric approaches in terms of fitting and predictive accuracy, and the optimal operating conditions recommended by our presented models are similar to those recommended in literature, which indicates the validation of our presented models. Copyright © 2012 John Wiley & Sons, Ltd.     

Surface mount digital package reliability

This paper compares the reliability of four surface mount package styles with the standard through-hole package. Three test boards were fabricated and subjected to environmental and electrical stresses. The relative package performances of SOICs, butt-soldered DIPs, surface mounted DIPS, and through-hole DIPs were found to be equal when subjected to stresses exceeding those expected in normal use. PLCC packages were found to be slightly less reliable in humidity environments than the other packages.     

基于响应面法的平底筒形件充液成形工艺参数优化

目的在板材充液成形过程中,压边间隙与最大液室压力的数值选取具有较大的随机性,同时由于材料的不同、坯料形状的差异,需要进行大量的仿真模拟来寻求优化结果。对于尺寸大、形状复杂的零件,模拟时间较长,工作效率较低。基于响应面法,构造压边间隙、最大液室压力与最大减薄率之间的响应面模型。方法以法兰外缘起皱高度为约束条件,通过Design-Expert软件求解最优结果,将最优结果进行了有限元模拟。结果模拟结果、响应值与试验结果相吻合。结论响应面法能够较好地用于预测和优化板材充液成形过程关键工艺参数。     

Simultaneous Optimization of Robust Parameter and Tolerance Design Based on Generalized Linear Models

Robust parameter design (RPD) and tolerance design (TD) are two important stages in design process for quality improvement. Simultaneous optimization of RPD and TD is well established on the basis of linear models with constant variance assumption. However, little attention has been paid to RPD and TD with non‐constant variance of residuals or non‐normal responses. In order to obtain further quality improvement and cost reduction, a hybrid approach for simultaneous optimization of RPD and TD with non‐constant variance or non‐normal responses is proposed from generalized linear models (GLMs). First, the mathematical relationship among the process mean, process variance and control factors, noise factors and tolerances is derived from a dual‐response approach based on GLMs, and the quality loss function integrating with tolerance is developed. Second, the total cost model for RPD‐TD concurrent optimization based on GLMs is proposed to determine the best control factors settings and the optimal tolerance values synchronously, which is solved by genetic algorithm in detail. Finally, the proposed approach is applied into an example of electronic circuit design with non‐constant variance, and the results show that the proposed approach performs better on quality improvement and cost reduction. Copyright © 2012 John Wiley & Sons, Ltd.     

The Impacts of Errors in Factor Levels on Robust Parameter Design Optimization

In robust parameter design (RPD), the ultimate goal is to identify the settings of control factors, which lead to an optimal mean with minimum process variation. In order to achieve this goal, usually two objective functions corresponding to the mean and variance of the desired quality characteristic are considered. Next, settings for the control variables (factors) are determined such that the values achieved for the two objective functions are as close to their ideal values as possible. This article highlights the impact of the miss‐specification of noise variables as fixed factors in RPDs. The miss‐specification or error in factor levels causes inappropriate estimates of the response model, which consequently affects the optimal settings of the control variables. The results are illustrated through an experimental example. Moreover, three different formulations are applied to determine the optimal settings for the case of Larger The Better (LTB). The performance of the formulations is also evaluated. Copyright © 2015 John Wiley & Sons, Ltd.     

基于响应面法的刀口金属密封结构优化设计

以有限元数值模拟为手段,通过一阶响应面建模,确定了满足密封判据的刀口金属密封结构设计参数的范围。采用均匀设计,建立了以设计参数为变量,以有效密封面宽、最大接触应力为响应的二阶响应面模型,并利用多目标优化方法和遗传算法,对响应面模型进行了优化求解,得到了优化的设计参数组合。有限元验证结果显示,优化后的密封结构具有更好的密封性能。     

基于作业成本法下SMT生产线成本的分析及应用

在对作业成本法原理分析的基础上,研究了计算机中使用的集成电路板SMT生产线的成本分配,提出了基于成本动因来划分SMT生产线成本的方法.这种方法为生产管理者提供了比较准确的成本信息,从而为有效控制产品成本,提高产品竞争能力打下基础.