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Experimentation was carried out using Taguchi based design of experiments (DOE) technique.
Taguchi based design of experiments approach was used for the aforementioned six parameters.
This paper addresses the topic of model based design of experiments for the identification of nonlinear dynamic systems.
The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE).
In this paper a novel analytic method for optimal model based design of experiments is presented, which can be applied to either nonlinear static or nonlinear dynamic systems.
Process models that are affected by uncertainties need a robust mechanism to account for them in the model based design of experiments (DOE).
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A response surface methodology (RS M – based design of experiment has been considered for this purpose.
A Box Behnken based design of experiment (DOE) method was used to generate data for development of a model.
Taguchi based design of experiment approach has been applied to optimize the parameters which is apposite for an optimal design towards efficient energy conversion.
Taguchi based design of experiment facilitates the finding of the most relevant information about the feature of the system to be optimized.
Full factorial based design of experiment focusing on input variables cutting speed, feed rate and cutting condition divulged 27 experimental runs.
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