• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3177-3183
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• 2013

This paper deals with the robust design of the non-asbestos FCM(Fiber-elastomer Coated Metal) gasket. In order to this, the measurement of the shear stress based on the design of experimet using the orthogonal table was carried out and the control factors for shear stress using the larger-the-better SN ratios with the Taguchi method were evaluated. In addition, the analysis of variance for SN ratios was conducted. The temperature, pressure, duration time and humidity were selected as the control factors. The orthogonal table $L_9(3^4)$ was made of 3 levels for each factor and the measurement of shear stress was acomplished on the base of the table. Delta statistics of time is the highest value 0.93 and therefore the time affect the largest effect on the shear stress of gasket. Also from the analysis, the shear stress shows maximun at the duration time 80 sec, temperature $200^{\circ}C$, pressure 90 $kgf/cm^2$, humidity 60 %RH. P values of duration time and temperature as a results of the analysis of variance are 0.037 and 0.098. Therefore the analysis has significant each with 95% and 90% confidence level.

• Fibers and Polymers
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• v.7 no.4
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• pp.344-351
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• 2006

This paper is intended to determine the optimal processing parameters applied to the dyeing procedure so that the desired color strength of a raw fabric can be achieved. Moreover, the processing parameters are also used for constructing a system to predict the fabric quality. The fabric selected is the nylon and Lycra blend. The dyestuff used for dyeing is acid dyestuff and the dyeing method is one-bath-two-section. The Taguchi quality method is applied for parameter design. The analysis of variance (ANOVA) is applied to arrange the optimal condition, significant factors and the percentage contributions. In the experiment, according to the target value, a confirmation experiment is conducted to evaluate the reliability. Furthermore, the genetic algorithm (GA) is combined with the back propagation neural network (BPNN) in order to establish the forecasting system for searching the best connecting weights of BPNN. It can be shown that this combination not only enhances the efficiency of the learning algorithm, but also decreases the dependency of the initial condition during the network training. Most of all, the robustness of the learning algorithm will be increased and the quality characteristic of fabric will be precisely predicted.

• Journal of the Korean Ceramic Society
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• v.39 no.6
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• pp.582-588
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• 2002

IrO$_2$-RuO$_2$ films were deposited on plasma sprayed TiO$_2$ buffer layer above Ti metal by sol-gel and dip-coating method. Organic vehicle (ethyl cellulose and $\alpha$-terpineol) and glass frit were added to improve adherence of the coatings. Taguchi method and L$_{18}$ (2$^1$$\times$3$^{7}$ ) orthogonal arrays were evalvated in terms of current density to determine the optimal combination of levels of factors that best satisfy the bigger is better quality characteristic. The observed conditions were as fellows: ethyl cellulose (100 cp), drying temperature and time (17$0^{\circ}C$,20 min), heat treatment temperature and time (75$0^{\circ}C$,10 min), the weight ratio of IrO$_2$-RuO/powders to glass frit (99:5), final heat treatment time (120 min) and flow rate of air (5 sccm), respectively. ANOVA analysis suggested that the influence of the factors within $\alpha$= 0.1 was significant with a 90% confidence level.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.130-136
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• 2001

Generally, a metal slitting saw is plain milling cutter with thickness less than 3/16 inch. This is used for cutting a workpiece that high dimensional accuracy and surface finish is necessary. A small thin milling cutter like a metal slitting saw is useful for machining a narrow groove. In this case, built up edge(BUE) is severe at each tooth and affects the surface integrity of the machined surface and tool wear. It is well known that tool geometry and cutting conditions are decisive factors to remove BUE. In this paper, we optimized the geometry of the milling cutter and selected cutting conditions to remove BUE by the experimental investigation. The experiment was planned with Taguchi method based on the orthogonal array of design factors such as coating, rake angle, number of tooth, cutting speed, feed rate. Response table was obtained from the number of built-up edge generated at tooth. The optimized tool geometry and cutting conditions could be determined through response table. In addition, the relative effect of factors was identified bh the analysis of variance (ANOVA). Finally, coating and cutting speed turned out important factors for BUE.

• Journal of Welding and Joining
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• v.35 no.1
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• pp.74-78
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• 2017

In auto ancillary fabrication industry, GMAW is a very useful & important welding process and EN10025 S 235 Grade is common material used for manufacturing of two wheeler chassis. This research gives the detail influence of welding process parameters such as welding current, welding voltage, wire speed on the penetration in EN10025 S 235 Grade mild steel material. The experimentation of this research has been carried out by using three factors, three level Taguchi DOE method. To analyze & optimize the welding parameters & characteristics, analysis of variance, L9 orthogonal array & signal to noise ratio are used. Length of Penetration in addition to the depth of penetration is major concern in fillet welded joints, as the penetration decides the strength of the welded joint. After analysis of penetration in all 9 welded samples, optimize parameters readings verified & found probability value within 0.05.From this research it is come to know that welding current & welding voltage is major parameters which affects the penetration in welded joints.

• Composites Research
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• v.29 no.1
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• pp.7-15
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• 2016

The quality of polymeric automotive parts depends highly on an injection molding process, which causes various defects, such as warpage, sink marks, weld lines, shrinkage, residual stress, etc. This study is to determine the optimum processing parameters, such as packing pressure, mold temperature, melting temperature, and packing time for the manufacture of polycarbonate buttons in cars on the basis of FEM, the Taguchi method, and analysis of variance (ANOVA). As a result, the optimum processing parameters of buttons made of polycarbonate material were obtained as follows: 140 MPa of packing pressure, $105^{\circ}C$ of mold temperature, $292.5^{\circ}C$ of melting temperature and 1 second of packing time. A gain of S/N (signal to noise) ratio, 10.2, was obtained with the optimum values. Moreover, the melting temperature was found to be the most significant factor followed by the mold temperature.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1362-1365
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• 2003

On this study. we improved the efficiency applying algorithm that is repeatedly using orthogonal array in discrete design space and filling a defect of gradient method in continuous design space. we showed optimal ply angle that maximized buckling strength of CFRP laminated composite plate without a hole and with a hole by each aspect ratio. In the case of CFRP laminated composite plate without a hole, we confirmed the reliance and efficiency of algorithm in comparison with the result optimization achievement repeatedly using statistical orthogonal array of experimental design.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.4 s.121
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• pp.324-332
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• 2007

Sensor placement method for damage identification has been developed for model updating using Taguchi method. In order to select the optimal sensor location, the analysis of variance of objective function using orthogonal array was carried out. Then, modal data at the selected locations were used for damage identification using model updating. The numerical model of a cantilever beam was used in order to compare the damage identification results with conventional sensor location method.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.171-178
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• 2014

From now on, in order to meet more stringer diesel emission standard, diesel vehicle should be equipped with emission after-treatment devices as NOx reduction catalyst and particulate filters. Urea-SCR is being developed as the most efficient method of reducing NOx emissions in the after-treatment devices of diesel engines, and recent studies have begun to mount the urea-SCR device for diesel passenger cars and light duty vehicles. That is because their operational characteristics are quite different from heavy duty vehicles, urea solution injection should be changed with other conditions. Therefore, the number and diameter of the nozzle, injection directions, mounting positions in front of the catalytic converter are important design factors. In this study, major design parameters concerning urea solution injection in front of SCR are optimized by using a CFD analysis and Taguchi method. The computational prediction of internal flow and spray characteristics in front of SCR was carried out by using STAR-CCM+7.06 code that used to evaluate $NH_3$ uniformity index($NH_3$ UI). The design parameters are optimized by using the $L_{16}$ orthogonal array and small-the-better characteristics of the Taguchi method. As a result, the optimal values are confirmed to be valid in 95% confidence and 5% significance level through analysis of variance(ANOVA). The compared maximize $NH_3$ UI and activation time($NH_3$ UI 0.82) are numerically confirmed that the optimal model provides better conversion efficiency of $NH_3$. In addition, we propose a method to minimize wall-wetting around the urea injector in order to prevent injector blocks caused by solid urea loading. Consequently, the thickness reduction of fluid film in front of mixer is numerically confirmed through the mounting mixer and correcting injection direction by using the trial and error method.