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Mean Square Error Criteria to Multiple Quality Characteristics Robust Design by the Weighted Tchebycheff Method

机译:均方误差标准以多种质量特征强制设计加权Tchebycheff方法

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Robust design has been widely applied in quality improvement. For most products, quality is multidimensional. Little attention has been paid to multiple quality characteristics robust design (MQCRD). MQCRD mainly faces two problems: measurement model and multiple objectives optimization. In order to give an appropriate measurement criterion and generate better Pareto solutions, a MQCRD model by the Weighted Tchebycheff method based on the mean square error (MSE) criterion is proposed. Firstly the MSE estimations for each quality characteristic are obtained by response surface method (RSM) and a MQCRD model based on the MSE criteria is given. Then a MQCRD model by the Weighted Tchebycheff method is present, which minimizes the distance between objective functions and the idea point based on the weighted infinite norm. The proposed approach could find very efficient Pareto solutions. Illustrative example shows the model can generate more efficient and robust solutions than the weighted-sum approach. Furthermore it has better results than the generalized reduced gradient (GRG) and quadratic loss function approach.
机译:强大的设计已广泛应用于质量改进。对于大多数产品,质量是多维的。一点关注多重质量特征强大的设计(MQCRD)。 MQCRD主要面临两个问题:测量模型和多目标优化。为了给出适当的测量标准并产生更好的帕累托解决方案,提出了基于平均方误差(MSE)标准的加权Tchebycheff方法的MQCRD模型。首先,通过响应表面方法(RSM)获得每个质量特性的MSE估计,并给出基于MSE标准的MQCRD模型。然后,存在由加权Tchebcheff方法的MQCRD模型,这最小化了基于加权无限规范的目标函数与思想点之间的距离。所提出的方法可以找到非常有效的帕累托解决方案。说明性示例显示了模型可以产生比加权和方法更有效和强大的解决方案。此外,它具有比广义减少的梯度(GRG)和二次损失功能方法更好的结果。

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