Statistical modal analysis for variation characterization and application in manufacturing quality control

被引：34

作者：

Huang, Wenzhen ^{[1
]}

Liu, Jinya ^{[1
]}

Chalivendra, Vijya ^{[1
]}

Ceglarek, Darek ^{[2
]}

Kong, Zhenyu ^{[3
]}

Zhou, Yingqing ^{[4
]}

机构：

[1] Univ Massachusetts Dartmouth, Dept Mech Engn, N Dartmouth, MA 02747 USA

[2] Univ Warwick, Int Digital Lab, WMG, Coventry CV4 7AL, W Midlands, England

[3] Oklahoma State Univ, Sch Ind & Management Engn, Stillwater, OK 74078 USA

[4] Dimens Control Syst Inc, Troy, MI 48084 USA

来源：

IIE TRANSACTIONS | 2014年 / 46卷 / 05期

基金：

美国国家科学基金会; 英国工程与自然科学研究理事会;

关键词：

Manufacturing; quality; variation reduction; GD&T tolerancing; DISCRETE-COSINE-TRANSFORM; GEOMETRIC TOLERANCES; POLYHEDRAL OBJECTS; ASSEMBLY PROCESSES; VARIATION MODEL; REPRESENTATION; PARTS;

D O I：

10.1080/0740817X.2013.814928

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A Statistical Modal Analysis (SMA) methodology is developed for geometric variation characterization, modeling, and applications in manufacturing quality monitoring and control. The SMA decomposes a variation (spatial) signal into modes, revealing the fingerprints engraved on the feature in manufacturing with a few truncated modes. A discrete cosine transformation approach is adopted for mode decomposition. Statistical methods are used for model estimation, mode truncation, and determining sample strategy. The emphasis is on implementation and application aspects, including quality monitoring, diagnosis, and process capability study in manufacturing. Case studies are conducted to demonstrate application examples in modeling, diagnosis, and process capability analysis.

引用

页码：497 / 511

页数：15

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