• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1263-1272
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• 2016

Product array approach which is used in the Taguchi parameter design has a number of advantages by considering the noise factor. However, a disadvantage of this method is that it requires an excessively large number of experiments. So combined array approach have been proposed to reduce the number of experiments. Taguchi has used the signal-to-noise ratio to find the optimum conditions in the Taguchi parameter design. In analyzing the data from the parameter design various problems tends occur by using an SN. In this paper, we propose an alternative solution for reducing the number of experiments without depending on the signal-to-noise ratio to overcome the shortcomings of the parameter design. Two examples illustrate this procedure in the two different experimental design (product array, combined array) approaches.

• Advances in materials Research
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• v.5 no.2
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• pp.67-80
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• 2016

The objective of the present work is to optimize process parameters namely, cutting speed, feed rate, and depth of cut in milling of AISI 304 stainless steel. In this work, experiments were carried out as per the Taguchi experimental design and an $L_{27}$ orthogonal array was used to study the influence of various combinations of process parameters on surface roughness (Ra) and material removal rate (MRR). As a dynamic approach, the multiple response optimization was carried out using grey relational analysis (GRA) and desirability function analysis (DFA) for simultaneous evaluation. These two methods are considered in optimization, as both are multiple criteria evaluation and not much complicated. The optimum process parameters found to be cutting speed at 63 m/min, feed rate at 600 mm/min, and depth of cut at 0.8 mm. Analysis of variance (ANOVA) was employed to classify the significant parameters affecting the responses. The results indicate that depth of cut is the most significant parameter affecting multiple response characteristics of GFRP composites followed by feed rate and cutting speed. The experimental results for the optimal setting show that there is considerable improvement in the process.

• Journal of Navigation and Port Research
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• v.35 no.2
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• pp.121-130
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• 2011

The localization of vehicle is an important part of an unmanned vehicle control problem. Pseudolite ultrasonic system(PUS) is the method to find an absolute position with a high accuracy by using ultrasonic sensor. And Gyro is the inertial sensor to measure yaw angle of vehicle. PUS can be able to estimate the position of mobile robot precisely, in which errors are not accumulated. And Gyro is a more faster measure method than PUS. In this paper, we suggest a more accuracy method of calculating PUS which is numerical analysis approach named Newtonian method. And also propose the fusion method to increase the accuracy of estimated angle on moving vehicle by using PUS and Gyro integrated system by Kalman filtering. To control the 4WS unmanned vehicle, the trajectory following algorithm is suggested. And the new concept arbitration of goal controller is suggested. This method considers the desirability function of vehicle state. Finally, the performances of Newtonian method and designed controller were verified from the experimental results with the 4WS vehicle scaled 1/10.

• Structural Engineering and Mechanics
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• v.76 no.5
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• pp.561-578
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• 2020

The present work addresses the surface integrity and chip morphology in finish hard turning of AISI D3 steel under nanofluid assisted minimum quantity lubrication (NFMQL) condition. The surface integrity aspects include microhardness, residual stress, white layer formation, machined surface morphology, and surface roughness. This experimental investigation aims to explore the feasibility of low-cost multilayer (TiCN/Al2O3/TiN) coated carbide tool in hard machining applications and to assess the propitious role of minimum quantity lubrication using graphene nanoparticles enriched eco-friendly radiator coolant based nano-cutting fluid for machinability improvement of hardened steel. Combined approach of central composite design (CCD) - analysis of variance (ANOVA), desirability function analysis, and response surface methodology (RSM) have been subsequently employed for experimental investigation, predictive modelling and optimization of surface roughness. With a motivational philosophy of "Go Green-Think Green-Act Green", the work also deals with economic analysis, and sustainability assessment under environmental-friendly NFMQL condition. Results showed that machining with nanofluid-MQL provided an effective cooling-lubrication strategy, safer and cleaner production, environmental friendliness and assisted to improve sustainability.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.521-533
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• 2023

In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

• The Korean Journal of Food And Nutrition
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• v.30 no.2
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• pp.319-325
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• 2017

In this study, we optimized the coffee extraction conditions for instant coffee production in two stage percolators, which is the most common coffee extractor for instant coffee production. A central composite design was used to build mathematical model equations for response surface methodology (RSM). In these equations, the yield and overall acceptability of the coffee extracts were expressed as second-order functions of three factors, the feed water temperature, draw-off factor (DOF), and extraction time (cycle time). Based on the result of RSM, the optimum conditions were obtained with the use of desirability function approach (DFA) which find the best compromise area among multiple options. The optimum extraction conditions to maximize the yield and overall acceptability over 40% of yield were found with $163^{\circ}C$ of feed water temperature, 4.3 of DOF and 27 minutes of extraction time (cycle time). These results provide a basic data for the coffee extraction conditions for the competitive instant coffee in the industry.

• Journal of Korean Society for Quality Management
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• v.42 no.4
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• pp.757-768
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• 2014

Purpose: In this paper we present a case study of developing fast curing adhesives for insulation material of LNG carriers using an extreme vertices design with four mixture components. Three material properties are considered - shear strength, viscosity, and tensile strength. In the optimization experiment, we used hardness instead of tensile strength due to shortage of specimens. Methods: We employ four-factor extreme vertices design with 19 runs and desirability function approach for simultaneously optimizing three responses. After selecting optimal condition of the mixture components, we do confirmation experiments to verify the reproducibility of the optimal condition under manufacturing circumstance. Results: Simultaneous optimal condition for the three responses, that is, shear strength, viscosity, and harness is obtained. At the optimal condition, confirmation experiments are executed in manufacturing circumstance. The variation for the shear strength is not satisfactory, which is due to the variation of the humidity. Conclusion: At the optimal condition three material properties are satisfactory. To reduce the variability for the shear strength, robust design is needed.

• Culinary science and hospitality research
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• v.24 no.1
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• pp.140-150
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• 2018

In this study, effects of microground coffee on the quality characteristics and acceptability of instant coffee with probiotics were investigated. A central composite design with two factors (roasting degree and dose of microground coffee) was used and ranges of roasting degree and dose were 30~50 (L value) and 5~10% respectively. Aroma preference, sweetness intensity, bitterness intensity, acidity intensity, body intensity and overall acceptability were evaluated as sensory characteristics and quadratic regression models of all the properties were significant. Especially in aroma preference and overall acceptability, the higher roasting degree and dose of microground coffee, the more aroma preference and overall acceptability of the coffee increased. And this results accorded with the object of this study to increase aroma preference and overall acceptability by blending microground coffee with instant coffee. On the other hand, 129 of aroma compounds were detected in instant coffee with microground coffee but 2,5-dimethyl-pyrazine, ethyl-pyrazine and furfural were significant in quadratic regression models. The optimal conditions were predicted by response surface methodology and desirability function approach and the optimal conditions of roasting degree and dose of microground coffee were 30(L value), 8.4%(w/w) respectively to maximize 2 sensory characteristics (overall preference, aroma preference) and 3 aroma components (2,5-dimethyl-pyrazine, ethyl-pyrazine, furfural).