A robustness coefficient is introduced which is designed to deal with the sensitivity of an optimised response towards small variations in the design variables. This robustness coefficient takes account of the variance with which the design variables can be set to a value. A particular problem arises, especially in the area of optimization of mixture experiments. The variance / covariance structure of the error with which the design variables can be set to a predefined value varies over the design space. The robustness coefficient is capable of dealing with this phenomenon
This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimiz...
Robust design (parameter design), originally proposed by Taguchi, is a quality engineering method fo...
In process robustness studies, it is desirable to minimize the influence of noise factors on the sys...
A robustness coefficient is introduced which is designed to deal with the sensitivity of an optimise...
The robustness coefficient (RC) introduced in Part I is an optimization criterion measuring the robu...
The robustness coefficient (RC) introduced in Part I is an optimization criterion measuring the robu...
The influence of a number of parameters on the behaviour of the robustness coefficient, introduced i...
Robustness of an object is defined as the probability that an object will have properties as require...
In a product system, large numbers of design variables and responses are involved in performance ana...
Robust optimization determines how the input variables dispersion is propagated on the output variab...
Designing a production process normally is involved with some important constraints such as uncertai...
Uncontrollable variations are unavoidable in engineering design. If ignored, such variations can ser...
This paper present a hew robust design optimization method based on robust performance variation est...
Robustness or insensitivity is a desirable property of decisions; however, most texts on robustness ...
Robust designs are more insensitive to the influence of variation in e.g. assembly, components and u...
This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimiz...
Robust design (parameter design), originally proposed by Taguchi, is a quality engineering method fo...
In process robustness studies, it is desirable to minimize the influence of noise factors on the sys...
A robustness coefficient is introduced which is designed to deal with the sensitivity of an optimise...
The robustness coefficient (RC) introduced in Part I is an optimization criterion measuring the robu...
The robustness coefficient (RC) introduced in Part I is an optimization criterion measuring the robu...
The influence of a number of parameters on the behaviour of the robustness coefficient, introduced i...
Robustness of an object is defined as the probability that an object will have properties as require...
In a product system, large numbers of design variables and responses are involved in performance ana...
Robust optimization determines how the input variables dispersion is propagated on the output variab...
Designing a production process normally is involved with some important constraints such as uncertai...
Uncontrollable variations are unavoidable in engineering design. If ignored, such variations can ser...
This paper present a hew robust design optimization method based on robust performance variation est...
Robustness or insensitivity is a desirable property of decisions; however, most texts on robustness ...
Robust designs are more insensitive to the influence of variation in e.g. assembly, components and u...
This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimiz...
Robust design (parameter design), originally proposed by Taguchi, is a quality engineering method fo...
In process robustness studies, it is desirable to minimize the influence of noise factors on the sys...