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Parameter Design with Asymmetric Loss Function under Normal Assumption

机译:正常假设下具有非对称损失函数的参数设计

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Taguchi developed many loss functions. Among these functions, the quadratic function is the most widely applied one. However, using a quadratic loss function when the actual loss function is nonquadratic might be choosing the incorrect input parameter levels. In certain situations, the linear loss function is more appropriate in industrial applications. In this paper, Asymmetric linear loss function is put forward under normal assumption. It's proved that Taguch's methods still work in this situation. Under normal assumption adjustment parameter is defined, and its best value is calculated which minionizes the fotal quality loss. Steps of parameter design are given.
机译:田口开发了许多损失函数。在这些函数中,二次函数是应用最广泛的函数。但是,当实际损失函数不是二次函数时,使用二次损失函数可能会选择错误的输入参数级别。在某些情况下,线性损耗函数更适合工业应用。本文在正常假设下提出了非对称线性损失函数。事实证明,Taguch的方法在这种情况下仍然有效。在正常假设下,定义了调整参数,并计算了其最佳值,该参数可最小化最终质量损失。给出了参数设计的步骤。

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