Researchers often identify robust design as one of the most effective engineering design methods for continuous quality improvement. When more than one quality characteristic is considered, an important question is how to trade off robust design solutions. In this paper, we consider a bi-objective robust design problem for which Pareto solutions of two quality characteristics need to be obtained. In practical robust design applications, a second-order polynomial model is adequate to accommodate the curvature of process mean and variance functions, thus mean-squared robust design models, frequently used by many researchers, would contain fourth-order terms. Consequently, the associated Pareto frontier might be non-convex and supported and no...
Abstract: Robust design optimization (RDO) uses statistical de-cision theory and optimization techni...
A UNIQUELY PRACTICAL APPROACH TO ROBUST DESIGN FROM A STATISTICAL AND ENGINEERING PERSPECTIVE Varia...
• Optimal design theory deals with the choice of the allocation of the observations to accomplish th...
In robust design optimization, if Taguchi quality loss function is employed, its expectation is mini...
Quality characteristics (QCs) are important product performance variables that determine customer sa...
The classic approach in robust optimization is to optimize the solution with respect to the worst ca...
Computational optimization for design is effective only to the extent that the aggregate objective f...
In design and optimization problems, a solution which is stable enough in its variability in presenc...
In this paper a framework for robust optimization of mechanical design problems and process systems ...
Engineering design often involves the optimization of different competing objectives. The aim is to ...
In realistic situations, engineering designs should take into consideration random aberrations from ...
Designing a production process normally is involved with some important constraints such as uncertai...
This paper addresses the dependency of design parameters and random variables within robust design o...
Robust design is a well-known quality improvement method that focuses on building quality into the d...
This paper proposes a method to compare the performances of different methods for robust design opti...
Abstract: Robust design optimization (RDO) uses statistical de-cision theory and optimization techni...
A UNIQUELY PRACTICAL APPROACH TO ROBUST DESIGN FROM A STATISTICAL AND ENGINEERING PERSPECTIVE Varia...
• Optimal design theory deals with the choice of the allocation of the observations to accomplish th...
In robust design optimization, if Taguchi quality loss function is employed, its expectation is mini...
Quality characteristics (QCs) are important product performance variables that determine customer sa...
The classic approach in robust optimization is to optimize the solution with respect to the worst ca...
Computational optimization for design is effective only to the extent that the aggregate objective f...
In design and optimization problems, a solution which is stable enough in its variability in presenc...
In this paper a framework for robust optimization of mechanical design problems and process systems ...
Engineering design often involves the optimization of different competing objectives. The aim is to ...
In realistic situations, engineering designs should take into consideration random aberrations from ...
Designing a production process normally is involved with some important constraints such as uncertai...
This paper addresses the dependency of design parameters and random variables within robust design o...
Robust design is a well-known quality improvement method that focuses on building quality into the d...
This paper proposes a method to compare the performances of different methods for robust design opti...
Abstract: Robust design optimization (RDO) uses statistical de-cision theory and optimization techni...
A UNIQUELY PRACTICAL APPROACH TO ROBUST DESIGN FROM A STATISTICAL AND ENGINEERING PERSPECTIVE Varia...
• Optimal design theory deals with the choice of the allocation of the observations to accomplish th...