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

机译:基于广义线性模型的鲁棒参数和公差设计同时优化

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摘要

Robust parameter design (RPD) and tolerance design (TD) are two important stages in design process for quality improvement. Simultaneous optimization of RPD and TO 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-normai 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.
机译:健壮的参数设计(RPD)和公差设计(TD)是设计过程中质量改进的两个重要阶段。在具有恒定方差假设的线性模型的基础上,可以很好地建立RPD和TO的同时优化。但是,对于RPD和TD的残差或非正常响应的变化不是很恒定,却很少关注。为了获得进一步的质量改进和成本降低,从广义线性模型(GLM)提出了一种同时优化RPD和TD且具有非恒定方差或非normai响应的混合方法。首先,从基于GLM的双响应方法推导了过程均值,过程方差和控制因子,噪声因子和公差之间的数学关系,并建立了与公差集成的质量损失函数。其次,提出了一种基于GLM的RPD-TD并发优化总成本模型,用于同步确定最优控制因子设置和最优容差值,并通过遗传算法对其进行详细求解。最后,将该方法应用于具有非恒定变化的电子电路设计实例,结果表明,该方法在质量改善和成本降低方面表现更好。

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