Optimal binning strategies under squared error loss in selective assembly with measurement error

Shun Matsuura, Nobuo Shinozaki

研究成果: Article査読

24 被引用数 (Scopus)

抄録

Selective assembly is an effective approach for improving a quality of a product assembled from two types of components, when the quality characteristic is the clearance between the mating components. Mease et al. (2004) have extensively studied optimal binning strategies under squared error loss in selective assembly, especially for the case when two types of component dimensions are identically distributed. However, the presence of measurement error in component dimensions has not been addressed. Here we study optimal binning strategies under squared error loss when measurement error is present. We give the equations for the optimal partition limits minimizing expected squared error loss, and show that the solution to them is unique when the component dimensions and the measurement errors are normally distributed. We then compare the expected losses of the optimal binning strategies with and without measurement error for normal distribution, and also evaluate the influence of the measurement error.

本文言語English
ページ(範囲)2863-2876
ページ数14
ジャーナルCommunications in Statistics - Theory and Methods
36
16
DOI
出版ステータスPublished - 2007 12 1

ASJC Scopus subject areas

  • Statistics and Probability

フィンガープリント 「Optimal binning strategies under squared error loss in selective assembly with measurement error」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル