• Journal of Integrative Natural Science
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• v.12 no.3
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• pp.69-73
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• 2019

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

• Journal of the Korean Data and Information Science Society
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• v.12 no.1
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• pp.11-18
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• 2001

Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used signal-to-noise(SN) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many statisticians criticize the Taguchi techniques of analysis, particularly those based on SN ratio. In this paper we propose a substantially simpler optimization procedure for parameter design without resorting to SN ratio.

• Journal of Integrative Natural Science
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• v.10 no.1
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• pp.51-57
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• 2017

The Taguchi parameter design in industry is an approach to reducing performance variation of quality characteristic in products and processes. In the Taguchi parameter design, the product array approach using orthogonal arrays is mainly used. It often requires an excessive number of experiments. An alternative approach, which is called the combined array approach, was studied. In these studies, only single response was considered. In this paper we propose how to simultaneously optimize multiresponse for the robust design using the combined array approach.

• Journal of Korean Society for Quality Management
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• v.29 no.4
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• pp.82-91
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• 2001

Taguchi robust design is widely used to quality improve methods. Especially, interest of dynamic characteristics parameter design is getting grow. In this paper, we have a comparative analyzed three Signal-to-Noise Ratios which are used in American Supplier Institute(ASI), MINITAB and Taguchi series published by Japanese Standard Institute with numerical examples.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.638-642
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• 2003

This paper presents a parameter design of an Electrorheological(ER) panel for noise reduction using Taguchi method. Taguchi method is a robust design method that determines control parameters in the presence of noise effect. Host structure thickness, spacer thickness, base oil viscosity and the weight ratio of ER particles are chosen for the control factors. A test setup in an SAE J1400 facility is used to analyze the sound transmission loss. The sensitivity of each factor with signal-to-noise(S/N) ratio and analysis of variance are investigated. The analysis results show that the weight ratio of ER particle and base oil viscosity of the ER fluid mostly affects the noise reduction in the presence of electric field. Based on the Taguchi method, an optimal configuration was designed and comparison is made with experimental result fer the verification.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.647-653
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• 2009

Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used SN (Signal to Noise) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. This paper describes the prediction technique of vehicle performance using parameter analysis to reduce man hour and test development period as well as to achieve stable NVH performance. Design engineer could efficiently decide the design variable using parameter analysis database in early design stage. These improvements can reduce the time needed to develop better vehicles.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.119-124
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• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.436-439
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• 2007

This paper describes the optimization of PGS(Patterned Ground Shield) of 5.5 turns rectangular spiral inductor using Taguchi's method. PGS is decrease method of parasite component by silicon substrate among dielectric loss reduction method. By using the taguchi's method, each parameter is fixed upon that PGS high poison(A), slot spacing(B), strip width(C) and overlap turn number(D) of PGS design parameter. Then we verified that percentage contribution and design sensitivity analysis of each parameter and level by signal to noise ratio of larger-the-better type. We consider percentage contribution and design sensitivity of each parameter and level, and then verify that model of optimization for PGS is lower inductance decreasing ratio and higher Q-factor increasing ratio by EM simulation.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.165-194
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• 1999

Taguchi's parameter design seeks proper choice of levels of controllable factors (Parameters in Taguchi's terminology) that makes the qualify characteristic of a product optimal while making its variability small. This aim can be achieved by response surface techniques that allow flexibility in modeling and analysis. In this article, a collection of response surface modeling and analysis techniques is proposed to deal with the multiresponse optimization problem in experimentation with Taguchi's signal and noise factors.

• Journal of Integrative Natural Science
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• v.11 no.2
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• pp.76-81
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• 2018

Robust design is an approach to reducing performance variation of quality characteristic values in quality engineering. Product array approach which is used in the Taguchi parameter design has a number of advantages by considering the noise factor. Taguchi has an idea that mean and variation are handled simultaneously to reduce the expected loss in products and processes. Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design using desirability function without resorting to SN.