Browsing by Subject "Taguchi methods"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Characterization of Shape Memory Alloys Using Artificial Neural Networks(2014-04-28) Henrickson, James VShape memory alloys are capable of delivering advantageous solutions to a wide range of engineering-based problems. Implementation of these solutions, however, is often complicated by the hysteretic, non-linear, thermomechanical behavior of the material. Existing constitutive models are largely capable of accurately describing this unique behavior, but they require prior characterization of material parameters. Current characterization procedures necessitate extensive data collection and data processing, creating a high barrier of entry for shape memory alloy application. This thesis develops a novel approach in which a form of computational intelligence is applied to the task of shape memory alloy material parameter characterization. Specifically, this work develops a methodology in which an artificial neural network is trained to identify transformation temperatures and stress influence coefficients of shape memory alloy specimens using strain-temperature coordinates as inputs. Training data is generated through the use of an existing shape memory alloy constitutive model. Factorial and Taguchi-based methods of generating training data are implemented and compared. Results show that trained artificial neural networks are capable of identifying shape memory alloy material parameters with satisfactory accuracy. Comparison of the implemented training data generation methods indicates that the Taguchi-based approach yields an artificial neural network that outperforms that of the factorial-based approach despite requiring significantly fewer training data specimens.Item Exposure of soft defects in integrated circuits using Taguchi methods(Texas Tech University, 2001-05) Towle, Christopher M.The work of Taguchi for determining the optimal settings of controllable factors through off-line experiments focuses on products with a single quality characteristic or response. However, most products have several quality characteristics or responses of interest. Taguchi's technique in itself optimizes a single response or performance characteristic yielding a set of process parameters. This particular setting may not give desired results for other characteristics of the product. In such cases, a need arises to obtain a single setting (optimal setting) of the process parameters, which can be used to produce the products with optimum or near optimum quality characteristics as a whole. Multi-characteristic response optimization may be the solution of the above problem. In the present paper a case study on frequency shift in a microprocessor is investigated utilizing a simplified multi-criterion methodology based on Taguchi's approach and utility concept, is discussed.