2000 Mathematics Subject Classification: 62J05, 62J10, 62F35, 62H12, 62P30.The model-based robust approach for improving the quality of the process is successfully applied to different industrial processes. In the case of multiple correlated responses the estimation of the mean and variance models of the quality characteristics in production conditions, taking into account the correlation between the multiple responses, together with the heteroscedasticity of the observations due to errors in the factor levels is considered at multivariate regression fit, robust engineering modeling and the optimization stages. The application of the proposed method gives the possibility to use raw industrial data for mean and variance models estimation and...
WOS: 000377032200009Most of the published literature on robust design is basically concerned with a ...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includ...
The analysis of robust parameter design is discussed via a model incorporating mean-variance relatio...
Many industrial firms seek the systematic reduction of variability as a primary means for reducing p...
[[abstract]]Conventional robust designs set parameters individually without considering feasible reg...
In a product system, large numbers of design variables and responses are involved in performance ana...
Quadratic loss functions have been used extensively within the context of quality engineering and ex...
Robust design (parameter design), originally proposed by Taguchi, is a quality engineering method fo...
Design of Experiments (DoE) is widely used in design, manufacturing and quality management. The resu...
The quality revolution of the late 80' s and 90' s led to researches in quality improvement in produ...
Robust design methodology aims at reducing the variability in the product performance in the presenc...
Robust parameter design is an effective tool to determine the optimal operating conditions of a syst...
Product and process designers need to find most preferable settings of design parameters to simultan...
Digitalisation of industrial processes, also called the fourth industrial revolution, is leading to ...
Parameter design optimization that involves two or more responses of products or processes is a well...
WOS: 000377032200009Most of the published literature on robust design is basically concerned with a ...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includ...
The analysis of robust parameter design is discussed via a model incorporating mean-variance relatio...
Many industrial firms seek the systematic reduction of variability as a primary means for reducing p...
[[abstract]]Conventional robust designs set parameters individually without considering feasible reg...
In a product system, large numbers of design variables and responses are involved in performance ana...
Quadratic loss functions have been used extensively within the context of quality engineering and ex...
Robust design (parameter design), originally proposed by Taguchi, is a quality engineering method fo...
Design of Experiments (DoE) is widely used in design, manufacturing and quality management. The resu...
The quality revolution of the late 80' s and 90' s led to researches in quality improvement in produ...
Robust design methodology aims at reducing the variability in the product performance in the presenc...
Robust parameter design is an effective tool to determine the optimal operating conditions of a syst...
Product and process designers need to find most preferable settings of design parameters to simultan...
Digitalisation of industrial processes, also called the fourth industrial revolution, is leading to ...
Parameter design optimization that involves two or more responses of products or processes is a well...
WOS: 000377032200009Most of the published literature on robust design is basically concerned with a ...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includ...
The analysis of robust parameter design is discussed via a model incorporating mean-variance relatio...