Premium
An Analytical Robust Design Optimization Methodology Based on Axiomatic Design Principles
Author(s) -
Cheng Qiang,
Xiao Chuanming,
Zhang Guojun,
Gu Peihua,
Cai Ligang
Publication year - 2014
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1534
Subject(s) - axiomatic design , axiom independence , mathematical optimization , dependency (uml) , computer science , axiom , scheme (mathematics) , design of experiments , matrix (chemical analysis) , optimal design , variation (astronomy) , design matrix , mathematics , engineering , artificial intelligence , machine learning , mathematical analysis , operations management , statistics , geometry , materials science , physics , lean manufacturing , astrophysics , linear regression , composite material
Robust design (RD) is an important method because it can reduce the variation of products or processes and improve their performances such as static and dynamic quality characteristics at a low cost. In order to obtain an efficient and universal RD solution, a novel analytical RD methodology is proposed based on axiomatic design principles. The covariance matrix of multiple functional requirements (FRs) that can reflect dependency relationship is obtained via the Talyor series expansion. Evaluation mechanism based on information axiom is introduced to select the better design scheme gained with different robust optimization models. The distinct characteristics of the proposed method are the implementation by matrix differential, and the ability that can deal with multiple FR optimization simultaneously. An RD optimization of a five roller coating head is illustrated. The results show that the proposed method can optimize the design parameters which meet the multiple FRs. Copyright © 2013 John Wiley & Sons, Ltd.