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Optimal Process Targets for Two Quality Characteristics under Considering the Variance of Empirical Loss

机译:考虑经验损失方差的两种质量特性的最佳工艺目标

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For the manufacturer wants to get the lowest total costs, increase productivity and improve product quality, the selection of the optimal process target is one of the key research problems. The traditional method solving this problem involves using a quality loss function, for example regression analysis that based on historical data concerning customer loss associated with product performance. However, the influence of empirical loss's fluctuation on the optimal process target's selection is typically neglected. In this study, based on the previous research, we consider two quality characteristics under considering the variance of empirical loss. A bivariate empirical loss function is developed, in which, the empirical loss's fluctuation range is divided into several intervals and regard them as restrictions. Then we build the optimal model to find out the corresponding economical process targets, and explore the effect of the variance of empirical loss on the industrial production. The effectiveness of the proposed approach is illustrated by an example. The results show that the size of the variance of the empirical loss has a significant impact on the cost of the production process.
机译:对于制造商来说,要获得最低的总成本,提高生产率并提高产品质量,选择最佳工艺目标是关键的研究问题之一。解决该问题的传统方法涉及使用质量损失函数,例如基于与产品性能相关的客户损失的历史数据进行回归分析。但是,经验损失波动对最佳工艺目标选择的影响通常被忽略。在这项研究的基础上,基于先前的研究,我们在考虑经验损失方差的情况下考虑了两个质量特征。建立了一个二元经验损失函数,将经验损失的波动范围划分为几个区间,并将其作为约束。然后建立最优模型,找出相应的经济过程目标,并探讨经验损失方差对工业生产的影响。实例说明了该方法的有效性。结果表明,经验损失方差的大小对生产过程的成本有重大影响。

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