Quality characteristics (QCs) are important product performance variables that determine customer satisfaction. Their expected values are optimized and their standard deviations are minimized during robust design (RD). Most of RD methodologies consider only a single QC, but a product is often judged by multiple QCs. It is a challenging task to handle dependent and oftentimes conflicting QCs. This work proposes a new robustness modeling measure that uses the maximum quality loss among multiple QCs for problems where the quality loss is the same no matter which QCs or how many QCs are defective. This treatment makes it easy to model RD with multivariate QCs as a single objective optimization problem and also account for the dependence between QCs. The new method is then applied to problems where bivariate QCs are involved. A numerical method for RD with bivariate QCs is developed based on the first order second moment (FOSM) method. The method is applied to the mechanism synthesis of a four-bar linkage and a piston engine design problem.
Skip Nav Destination
Article navigation
October 2014
Research-Article
Robust Design for Multivariate Quality Characteristics Using Extreme Value Distribution
Changming Yang,
Changming Yang
Professor
School of Mechanical Engineering
and Automation,
e-mail: cmyang@163.com
School of Mechanical Engineering
and Automation,
Xihua University
,Chengdu 610039
, China
e-mail: cmyang@163.com
Search for other works by this author on:
Xiaoping Du
Xiaoping Du
1
Professor
Department of Mechanical
and Aerospace Engineering,
e-mail: dux@mst.edu
Department of Mechanical
and Aerospace Engineering,
Missouri University of Science
and Technology,
400 West 13th Street
,Toomey Hall 290D
,Rolla, MO 65409
e-mail: dux@mst.edu
1Corresponding author.
Search for other works by this author on:
Changming Yang
Professor
School of Mechanical Engineering
and Automation,
e-mail: cmyang@163.com
School of Mechanical Engineering
and Automation,
Xihua University
,Chengdu 610039
, China
e-mail: cmyang@163.com
Xiaoping Du
Professor
Department of Mechanical
and Aerospace Engineering,
e-mail: dux@mst.edu
Department of Mechanical
and Aerospace Engineering,
Missouri University of Science
and Technology,
400 West 13th Street
,Toomey Hall 290D
,Rolla, MO 65409
e-mail: dux@mst.edu
1Corresponding author.
Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received November 21, 2013; final manuscript received June 17, 2014; published online July 31, 2014. Assoc. Editor: David Gorsich.
J. Mech. Des. Oct 2014, 136(10): 101405 (8 pages)
Published Online: July 31, 2014
Article history
Received:
November 21, 2013
Revision Received:
June 17, 2014
Citation
Yang, C., and Du, X. (July 31, 2014). "Robust Design for Multivariate Quality Characteristics Using Extreme Value Distribution." ASME. J. Mech. Des. October 2014; 136(10): 101405. https://doi.org/10.1115/1.4028016
Download citation file:
Get Email Alerts
Cited By
Related Articles
Variation Source Identification in Manufacturing Processes Based on Relational Measurements of Key Product Characteristics
J. Manuf. Sci. Eng (June,2008)
Robustness of Design Through Minimum Sensitivity
J. Mech. Des (June,1992)
Sequential Design Process for Screening and Optimization of Robustness and Reliability Based on Finite Element Analysis and Meta-Modeling
J. Comput. Inf. Sci. Eng (August,2022)
Related Proceedings Papers
Related Chapters
Getting Ready for Production
Total Quality Development: A Step by Step Guide to World Class Concurrent Engineering
S/N (Signal-to-Noise) Ratios for Static Characteristics and the Robustness Optimization Procedure
Taguchi Methods: Benefits, Impacts, Mathematics, Statistics and Applications
Logarithm Transformation of the Output Response Data for Optimization
Taguchi Methods: Benefits, Impacts, Mathematics, Statistics and Applications