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Showing 1 to 14 of 14 for “"Robust parameter design"”.
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New design comparison criteria in Taguchi's robust parameter design
Choice of an experimental design is an important concern for most researchers. Judicious selection of an experimental design is also a weighty matter in Robust Parameter Design (RPD). RPD seeks to choose the levels of fixed controllable variables that provide insensitivity (robustness) to the …
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Robust Parameter Design for Automatically Controlled Systems and Nanostructure Synthesis
… comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and …
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A response surface approach to data analysis in robust parameter design
… of heterogeneous variability with standard design and modeling techniques available in response surface methodology.
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CONFIDENCE REGIONS FOR OPTIMAL CONTROLLABLE VARIABLES FOR THE ROBUST PARAMETER DESIGN PROBLEM
In robust parameter design it is often possible to set the levels of the controllable factors to produce a zero gradient for the transmission of variability from the noise variables. If the number of control variables is greater than the number of noise variables, a continuum of zero-gradient …
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Comparative analysis of robust design methods
Robust parameter design is an engineering methodology intended as a cost effective approach to improve the quality of products, processes and systems. Control factors are those system parameters that can be easily controlled and manipulated. Noise factors are those system parameters that are …
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Semiparametric Techniques for Response Surface Methodology
… to an elementary RSM problem as well as the robust parameter design problem.
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System regularities in design of experiments and their applications
… planning and analysis of experiments, and to robust design of engineering systems. Three previously observed properties are analyzed - effect sparsity, hierarchy, and heredity. A new regularity on effect synergism is introduced and shown to be statistically significant. It is shown that a …
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A quadrature-based technique for robust design with computer simulations
… for estimating transmitted variance to enable robust parameter design in computer simulations. This method is based on the Hermite-Gaussian quadrature for a single input. It is extended to multiple variables, in which case, for simulations with n randomly varying inputs, the method requires 4n …
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Resource Modeling and Allocation in Competitive Systems
… value of any bundle given limited information, design bidding strategies that efficiently select desirable bundles, and evaluate the performance of different bundling strategies under various market settings. In the second project Retailer shelf-space management with promotion effects, …
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Bayesian hierarchical modelling of dual response surfaces
… Taguchi (Tauchi (1985)) introduced the idea of robust parameter design on the quality improvement in the United States in mid-1980s. The original procedure is to use the mean and the standard deviation of the characteristic to form a dual response system in linear model structure, and to …
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Response surface designs and analysis for bi-randomization error structures
… error control format of which the split plot design is a special case. A bi-randomization scheme allows for certain factor levels to be applied at random to large experimental units with the remaining factor levels randomly applied to nested smaller units. For example, in the dual response …
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Robust parameter optimization strategies in computer simulation experiments
… now popularly known as the Taguchi Methods for robust parameter design. Following Taguchi's philosophy, the goal of this research is to devise a framework for finding optimum operating levels for the controllable input factors in a stochastic system that are insensitive to internal sources of …
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Contributions to quality improvement methodologies and computer experiments
… computer experiments, i.e., selective assembly, robust design with computer experiments, multivariate quality control, model selection for split plot experiments, and construction of minimax designs. Selective assembly has traditionally been used to achieve tight specifications on the clearance …