Optimal Partitioning of Probability Distributions under General Convex Loss Functions in Selective Assembly
Optimal Partitioning of Probability Distributions under General Convex Loss Functions in Selective Assembly
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DOI：
10.1080/03610920903581002
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发表时间：
2011-01-01
影响因子：
0.8
通讯作者：
Matsuura, Shun
中科院分区：
文献类型：
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作者：
Matsuura, Shun
选择性装配是提高由两个配合零件组成的产品质量的有效途径。研究了选择装配中零件尺寸分布的最优划分问题。推广了已有的平方误差损失函数的结果，使之适用于一般的凸损失函数，包括非对称凸损失函数。推导出最佳划分的方程。在维数分布的密度函数为对数凹的假设下，建立了解的唯一性，并证明了最优划分的一些性质。一些数值结果比较了一些启发式划分方案的最佳划分。
Selective assembly is an effective approach for improving the quality of a product which is composed of two mating components. This article studies optimal partitioning of the dimensional distributions of the components in selective assembly. It extends previous results for squared error loss function to cover general convex loss functions, including asymmetric convex loss functions. Equations for the optimal partition are derived. Assuming that the density function of the dimensional distribution is log-concave, uniqueness of solutions is established and some properties of the optimal partition are shown. Some numerical results compare the optimal partition with some heuristic partitioning schemes.