| Project/Area Number |
21710163
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | The Institute of Statistical Mathematics |
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Principal Investigator |
KAWAMURA Toshihiko The Institute of Statistical Mathematics, データ科学研究系, 助教 (70435494)
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| Project Period (FY) |
2009 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2010: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2009: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 社会システム工学 / 品質管理 / 品質工学 / パラメータ設計 / SN比 / 統計科学 / 統計的品質管理 / ロバストパラメータ設計 / 統計工学 |
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| Research Abstract |
In this article, we propose a statistical method which reduces the variation in measurement systems. We consider systems with positive-valued linear signal-response relationship passing through the origin. The unobservable noise variables are classified into three categories : noise factors, remained noise factors, and random errors. Then we propose a generalized signal-to-noise (SN) ratio in measurement systems with respect to the classification. Furthermore, we discuss the two different data analysis methods -response function modeling and performance measure modeling- for modeling and optimization. The effectiveness of two methods is investigated by a Monte Carlo simulation study.
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