Robust Parameter Design for Multivariate Quality Characteristics based on Process Capability Index with Individual Observations
Abstract
An integrated approach based on process capability index and entropy weight method is proposed to solve the robust parameter design for multivariate quality characteristics with individual observations. Firstly, assume that the design variables follow normal distributions and use the response surface method to build mean and variance models. Then the objective function based on process capability index is set up through analyzing the weight of deviation and variance with the entropy weight method. A numerical example shows that the optimal design variables obtained by the proposed approach could make quality characteristics satisfy the product specifications and close to the targets compared with other parameter design methods.
Recommended Citation
X. Gu et al., "Robust Parameter Design for Multivariate Quality Characteristics based on Process Capability Index with Individual Observations," Xi Tong Gong Cheng Yu Dian Zi Ji Shu Systems Engineering and Electronics, vol. 39, no. 2, pp. 362 - 368, Chinese Institue of Electronics, Feb 2017.
The definitive version is available at https://doi.org/10.3969/j.issn.1001-506X.2017.02.20
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Entropy weight method; Individual observations; Multivariate quality characteristics; Process capability index; Robust parameter design
International Standard Serial Number (ISSN)
1001-506X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Chinese Institute of Electronics, All rights reserved.
Publication Date
01 Feb 2017
