• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.99-111
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• 1994

Toguchi method is a systematic technique for designing high quality product at low cost. There are three steps in the Toguchi method, 1)system design, 2)parameter design, and 3)tolerance design. This paper considers the tolerance design for multiple performance characteristics which is practically important. We present two tolerance design procedures : grade selection and tolerance determining procedures. In grade selection procedure a scheme is presented that minimizes the sum of the price of low-level characteristics and the expected loss due to the variations of high-level characteristics. In tolerance determining procedure we determine the tolerances of the low-level characteristics.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.866-870
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• 2001

Measurement techniques for in-duct acoustic source parameters can be classified into the direct method and the load method, according to whether it utilizes an extra external source or not. It is reported that the load methods yield the negative source resistance and the purpose of this paper is to clarify that the time-varying nature of the source is the main cause of this physically implausible result. For this purpose, the direct and load methods for measuring the source characteristics of a simplified fluid machine are simulated using the time domain numerical analysis. In the numerical simulations, the method of characteristics is employed and the source characteristics are calculated from the resultant data. It is shown that the load method results in negative source resistance for some frequencies, whereas the direct method yields positive values for all frequencies considered. It is found that the result of load method is quite sensitive to the change of cylinder pressure or valve profile in contrast to the direct method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.494-499
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• 2003

This paper concerns the static, dynamic and thermal characteristics analysis of a high-speed spindle system for horizontal machining centers with 45mm x50,000rpm. The spindle system is designed based on the angular contact ceramic ball bearings, built-in motor, oil-air lubrication method and oil jacket cooling method. The structural and thermal analysis models of spindle system are constructed by the finite element method. The static and dynamic characteristics are estimated based on the static deformation, modal parameter, mode shape and frequency response function, and the thermal characteristics are estimated based on the temperature rise, temperature distribution and thermal deformation. The analysis results illustrate that the designed spindle system has excellent structural and thermal stabilities

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.808-813
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• 2007

We present the numerical characteristics of a new true stress-strain curve acquisition method over a large range of strains by the tensile test and a finite element method through comparing the results obtained by various finite element mesh systems. The method is introduced in detail. The effects of the finite element mesh systems on the results are investigated to show its numerical characteristics of the new method. It is shown that the method is quite robust, implying that it can be used as a special function of the tensile test machines.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.8
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• pp.731-735
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• 2002

Electro-optical (EO) performances for the twisted-nematic (TN)-liquid crystal display (LCD) photoaligned with linearly polarized UV exposure on the poly［4- (fluorocinnamate) phenylmaleimide](PFCPMI) surfaces using a new photodimerization method were investigated. For a new UVLPH (UV linearly polarized during heating) photodimerization method, the photopolymer layers were exposed by linearly polarized UV dichroic polarizer without a specific UV filter during heating at $150^{\circ}C$. The Voltage-transmittance (V-T) curve without backflow bounce in the photoaligned TN-LCD with UV exposure on the PFCPMI surface for 10 min using the UVLPH photodimerization method was observed. For response time measurement, the transmittance characteristics of the photoaligned TN-LCD using the UVLPH photodimerization method on the photopolymer surface was better than that of the photoaligned TN-LCD using the UVLP photodimerization method under a room temperature.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1520-1528
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• 2000

This study presents a method for determining bearing stiffness and damping coefficients of air-lubricated slider bearing, and shows influences of air-bearing surface geometry(recess depth, crown an d pivot location) on flying attitude and dynamic characteristics. To derive the dynamic lubrication equation, the perturbation method is applied to the generalized lubrication equation which based on linearized Boltzmann equation. The generalized lubrication equation and the dynamic lubrication equation are converted to a control volume formulation, and then, the static and dynamic pressure distributions are calculated by finite difference method. The recess depth and crown of the slider show significantly influence on flying attitude and dynamic characteristics comparing with those of pivot location.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2217-2220
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• 2003

It is known that an EEG is characterized by the unique and personal characteristics of an individual. Little research has been done to take into account these personal characteristics when analyzing EEG signals. Often the EEG has frequency components which can describe most of the significant characteristics. These combinations are often unique like individual human beings and yet they have an underlying basic characteristics as well. We think that these combinations are the personal characteristics frequency components of the EEG. In this seminar, the EEG analysis method by using the Genetic Algorithms (GA), Factor Analysis (FA), and the Neural Networks (NN) is proposed. The GA is used for selecting the personal characteristic frequency components. The FA is used for extracting the characteristics data of the EEG. The NN is used for estimating the characteristics data of the EEG. Finally, in order to show the effectiveness of the proposed method, classifying the EEG pattern is carried out via computer simulations. The EEG pattern is evaluated under 4 conditions: listening to Rock music, Schmaltzy Japanese ballad music, Healing music, and Classical music. The results, when personal characteristics frequency components are NOT used, gave over 80 % accuracy versus a 95 % accuracy when personal characteristics frequency components are used. This result of our experiment shows the effectiveness of the proposed method.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.213-219
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• 2018

Purpose: Satisfying the environmental regulations, the automobile manufacturer should install urea tank, which is a key component of the urea system. However, due to the limitations of existing layouts, it may be mounted which is disadvantageous to vibration and shock resulting in durability robust. analyze the factors affecting the durability life of urea tank and the vibration characteristics through RLDA. In this study, clarify the limit of the current practice test method of urea tank and analyze the possibility of the new vibration test method in the system unit reflecting the characteristics of actual use condition. Methods: Analyzing the factors affecting the durability life of urea tank and the vibration characteristics through PSD & FDS of RLDA that actual vehicle driving data on durability test road. Results: The limit of the uniform width/single frequency test method of urea tank is clarifed and the positive prospects of the new test method are discovered. Conclusion: The vibration durability test with PSD method in system unit effectively reflects the magnitude and frequency characteristics of field vibration.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.1
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• pp.28-42
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• 2017

Moisture transfer characteristics of high emotional garments are important to evaluate wear comfort. Wicking and drying measurement methods are also critical for perspiration absorption and quick dry fabric made of high functional fibers. In this study, the wicking and drying properties of high emotional fabrics made from hybrid composite yarns using CoolMax, Tencel, Bamboo staple fibers and PP. PET CoolMax filaments were also measured and analyzed according to various measuring methods. The wicking property of hybrid composite yarn fabrics by Bireck method was mostly influenced by the structure of hybrid yarns than the absorption rate of constituent fibers; however, both the hygroscopicity of fibers and the composite yarn structure affected the wicking property of the fabrics in the drop method. Concerning drying properties, the KSK 0815B method measuring distilled moisture weight was more relevant to explain the drying characteristics of hybrid yarn fabrics than the KSK 0815A method measuring the time to drying. This study revealed that the drying properties of hybrid yarn fabrics were influenced by the hygroscopicity of constituent fibers, wicking properties of constituent yarns and structure of composite yarns.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1085-1092
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• 2017

In this paper, we propose a wind forecasting method that reflects wind characteristics to improve the accuracy of wind power prediction. The proposed method consists of extracting wind characteristics and predicting power generation. The part that extracts the characteristics of the wind uses correlation analysis of power generation amount, wind direction and wind speed. Based on the correlation between the wind direction and the wind speed, the feature vector is extracted by clustering using the K-means method. In the prediction part, machine learning is performed using the SVR that generalizes the SVM so that an arbitrary real value can be predicted. Machine learning was compared with the proposed method which reflects the characteristics of wind and the conventional method which does not reflect wind characteristics. To verify the accuracy and feasibility of the proposed method, we used the data collected from three different locations of Jeju Island wind farm. Experimental results show that the error of the proposed method is better than that of general wind power generation.