The Experts below are selected from a list of 29637 Experts worldwide ranked by ideXlab platform
Chiaming Chang - One of the best experts on this subject based on the ideXlab platform.
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the use of grey based Taguchi Methods to determine submerged arc welding process parameters in hardfacing
Journal of Materials Processing Technology, 2002Co-Authors: Y S Tarng, S C Juang, Chiaming ChangAbstract:Abstract In this paper, the use of grey-based Taguchi Methods for the optimization of the submerged arc welding (SAW) process parameters in hardfacing with considerations of multiple weld qualities is reported. In this new approach, the grey relational analysis is adopted to solve the SAW process with multiple weld qualities. A grey relational grade obtained from the grey relational analysis is used as the performance characteristic in the Taguchi method. Then, optimal process parameters are determined by using the parameter design proposed by the Taguchi method. Experimental results have shown that optimal SAW process parameters in hardfacing can be determined effectively so as to improve multiple weld qualities through this new approach.
Ludwig J Hollick - One of the best experts on this subject based on the ideXlab platform.
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designing simulation experiments Taguchi Methods and response surface metamodels
Winter Simulation Conference, 1991Co-Authors: John S Ramberg, Susan M Sanchez, Paul J Sanchez, Ludwig J HollickAbstract:G. Taguchi (1987) has made an innovative contribution to quality planning activities through the integrated use of loss functions and orthogonal arrays. The authors focus on the improvement and implementation of some of these techniques in the simulation arena. The orthogonal arrays advocated by Taguchi are related to classical experimental designs, which have played important tactical roles in the exploration of mathematical metamodels for the simulation response surface. However, the loss function and the associated robust design philosophy provide fresh insights into the process of optimizing or improving the simulation's performance. The authors use examples to illustrate concepts such as the simultaneous treatment of variability and mean of performance measures, strategies for achieving system robustness, and implementation of noise through factorial designs. Relationships to other issues in designing and analyzing simulation experiments, such as response surface metamodels and variance reduction, are discussed. >
Avoki M Omekanda - One of the best experts on this subject based on the ideXlab platform.
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robust torque and torque per inertia optimization of a switched reluctance motor using the Taguchi Methods
IEEE Transactions on Industry Applications, 2006Co-Authors: Avoki M OmekandaAbstract:This paper presents the use of Taguchi Methods in optimizing a switched reluctance motor (SRM) for applications requiring fast actuation. In these applications, the SRM is designed to provide a high electromagnetic torque-to-inertia ratio required for high rates of mechanical acceleration. This is accomplished using two simultaneous robust optimizations of an SRM, namely: 1) an optimization of the motor torque and 2) an optimization of the torque per inertia (mechanical acceleration). The Taguchi two-step optimization method and the zero-point-proportional dynamic response were used successfully in the double optimization. Two orthogonal arrays were used to lead the design of experiments (DOE). Finite-element analysis was used to compute the performance of the motor designs generated by the Taguchi DOE.
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robust torque and torque per inertia optimization of a switched reluctance motor using the Taguchi Methods
International Electric Machines and Drives Conference, 2005Co-Authors: Avoki M OmekandaAbstract:This paper presents the use of Taguchi Methods for optimizing a switched reluctance motor (SRM) for applications requiring fast actuation. In these applications, the SRM is designed to provide a high electromagnetic torque to inertia ratio required for high rates of mechanical acceleration. This is accomplished through two simultaneous robust optimizations of a switched reluctance motor; that is, an optimization of the motor torque and an optimization of the torque-per-inertia (mechanical acceleration). The Taguchi two-step optimization method as well as the zero-point-proportional dynamic response were used successfully in the double optimization. Two orthogonal arrays (OA) were used to lead the design of experiments (DOE). Finite element analysis (FEA) was used to compute the performance of the motor designs generated by the Taguchi DOE
Y S Tarng - One of the best experts on this subject based on the ideXlab platform.
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the use of grey based Taguchi Methods to determine submerged arc welding process parameters in hardfacing
Journal of Materials Processing Technology, 2002Co-Authors: Y S Tarng, S C Juang, Chiaming ChangAbstract:Abstract In this paper, the use of grey-based Taguchi Methods for the optimization of the submerged arc welding (SAW) process parameters in hardfacing with considerations of multiple weld qualities is reported. In this new approach, the grey relational analysis is adopted to solve the SAW process with multiple weld qualities. A grey relational grade obtained from the grey relational analysis is used as the performance characteristic in the Taguchi method. Then, optimal process parameters are determined by using the parameter design proposed by the Taguchi method. Experimental results have shown that optimal SAW process parameters in hardfacing can be determined effectively so as to improve multiple weld qualities through this new approach.
C R Joyner - One of the best experts on this subject based on the ideXlab platform.
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application of Taguchi Methods to propulsion system optimization for ssto vehicles
Journal of Spacecraft and Rockets, 1992Co-Authors: Douglas O Stanley, R. Unal, C R JoynerAbstract:The application of advanced technologies to future launch vehicle designs would allow the introduction of a rocket-powered, single-stage-to-orbit (SSTO) launch system early in the next century* For a selected SSTO concept, a dual mixture ratio, staged combustion cycle engine was selected as the baseline propulsion system. A series of parametric trade studies are presented to optimize both a dual mixture ratio engine and a single mixture ratio engine of similar design and technology level. The effect of varying lift-off thrust-to-weight ratio, engine mode transition Mach number, mixture ratios, area ratios, and chamber pressure values on overall vehicle weight is examined. The sensitivity of the advanced SSTO vehicle to variations in each of these parameters is presented, taking into account the interaction of each of the parameters with each other. This parametric optimization and sensitivity study employs a Taguchi design method. The Taguchi method is an efficient approach for determining near optimum design parameters using orthogonal matrices from design of experiments (DOE) theory. Using orthogonal matrices significantly reduces the number of experimental configurations to be studied. The effectiveness and limitations of the Taguchi method are also discussed.
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application of Taguchi Methods to dual mixture ratio propulsion system optimization for ssto vehicles
30th Aerospace Sciences Meeting and Exhibit, 1992Co-Authors: Douglas O Stanley, R. Unal, C R JoynerAbstract:The application of advanced technologies to future launch vehicle designs would allow the introduction of a rocket-powered, single-stage-to-orbit (SSTO) launch system early in the next century. For a selected SSTO concept, a dual mixture ratio, staged combustion cycle engine that employs a number of innovative technologies was selected as the baseline propulsion system. A series of parametric trade studies are presented to optimize both a dual mixture ratio engine and a single mixture ratio engine of similar design and technology level. The effect of varying lift-off thrust-to-weight ratio, engine mode transition Mach number, mixture ratios, area ratios, and chamber pressure values on overall vehicle weight is examined. The sensitivity of the advanced SSTO vehicle to variations in each of these parameters is presented, taking into account the interaction of each of the parameters with each other. This parametric optimization and sensitivity study employs a Taguchi design method. The Taguchi method is an efficient approach for determining near-optimum design parameters using orthogonal matrices from design of experiments (DOE) theory. Using orthogonal matrices significantly reduces the number of experimental configurations to be studied. The effectiveness and limitations of the Taguchi method for propulsion/vehicle optimization studies as compared to traditional single-variable parametric trade studies is also discussed.
