• Journal of Power Electronics
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• v.18 no.1
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• pp.92-102
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• 2018

A sliding mode control (SMC) for servo motors based on the differential evolution (DE) algorithm, called DE-SMC, is proposed in this study. The parameters of SMC should be designed exactly to improve the robustness, realize the precision positioning, and reduce the steady-state speed error of the servo drive. The main parameters of SMC are optimized using the DE algorithm according to the speed feedback information of the servo motor. The most significant influence factor of the DE algorithm is optimization iteration. A suitable iteration can be achieved by the tested optimization process profile of the main parameters of SMC. Once the parameters of SMC are optimized under a convergent iteration, the system realizes the given performance indices within the shortest time. The experiment indicates that the robustness of the system is improved, and the dynamic and steady performance achieves the given performance indices under a convergent iteration when motor parameters mismatch and load disturbance is added. Moreover, the suitable iteration effectively mitigates the low-speed crawling phenomenon in the system. The correctness and effectiveness of DE-SMC are verified through the experiment.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.9 no.1
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• pp.87-93
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• 2004

In the design of mobile wireless communication network, BSC(Base Station Location), BSC(Base Station Controller) and MSC(Mobile Switching Center) are the most important parameters. Designing base station location, the cost must be minimized by combining various, complex parameters. We can solve this Problem by combining optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been used extensively for global optimization. This paper shows the 4 kinds of algorithm to be applied to the optimization of base station location for communication system and then compares, analyzes the results and shows optimization process of algorithm.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.321-322
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• 2002

This paper presents study of effects of cutting parameters such as cutting speed, feed rate and depth of cut on the surface roughness in hard turning. Taguchi Method and linear regression model of design parameters were utilized to identify the controlling process parameters that can monitor the surface roughness in the hard turning operation. In the process optimization, experimental planning was performed using the orthogonal array and concept of the signal-to-noise ratio. Cutting parameters such as speed, feed rate, and depth of cut were selected as process parameters and the ANOVA analysis showed that feed rate and cutting speed had more effect on the roughness variation that depth of cut.

• Transactions on Electrical and Electronic Materials
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• v.13 no.3
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• pp.129-135
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• 2012

A number of surface mount technology (SMT) process variables including land design are considered for minimizing tombstone defect in flexible printed circuit assembly in high volume manufacturing. As SMT chip components have been reduced over the past years with their weights in milligrams, the torque that once helped self-centering of chips, gears to tombstone defects. In this paper, we have investigated the correlation of the assembly process variables with respect to the tombstone defect by employing statistically designed experiment. After the statistical analysis is performed, we have setup hypotheses for the root causes of tombstone defect and derived main effects and interactions of the process parameters affecting the hypothesis. Based on the designed experiments, statistical analysis was performed to investigate significant process variable for the purpose of process control in flexible printed circuit manufacturing area. Finally, we provide beneficial suggestions for find-pitch PCB design, screen printing process, chip-mounting process, and reflow process to minimize the tombstone defects.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.4
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• pp.417-430
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• 2009

A BNR comprehensive performance evaluation (BNR CPE) system was established employing system-oriented evaluation methodology for biological nutrient removal (BNR) processes based on the CPE techniques developed by U.S. EPA for evaluation of conventional biological processes. The BNR CPE system applied to five domestic BNR plants adopting $A^2/O$ process confirmed that all target plants except the smallest one had not any serious defective performance and process stability was enhanced with increasing plant size. The system also clearly verified relatively poor performances in anoxic reactors without exception mainly due to influent carbon limit rather than functional defect. Consistent good performances were confirmed even during both winter season and wet weather generally known to be difficult to achieve satisfactory removals. Presentation of evaluation results by modified radar chart system simplified and clarified the evaluation and analysis procedures. The BNR CPE system could not only discover readily the causes of present and prospective poor performances but also facilitate the suggestion of their optimization options. Mutual effect and cause-and-effect among operation parameters and unit processes were also found easily using the evaluation system. The system justified that the adverse effect of defective operating parameters could be compensated by other favorable parameters, especially in anaerobic and anoxic reactors as well as during the winter season.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.507-516
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• 2000

In the present paper we consider a problem of choosing the rational way to carry on the metal processing (the problem of stochastic optimization) and the problem of determing the unknown characteristics of parameters described with random variables.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1763-1768
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• 2003

Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. Based on the independence axiom of axiomatic design theory that illustrates the relationship between desired specifications and design parameters, the designs can be classified into three types: uncoupled, decoupled and coupled. To best approach the target performance with the maximum robustness is one of the main functional requirements of a mechanical system. Most engineering designs are pertaining to either coupled or decoupled ones, but these designs cannot currently accomplish a real robustness thus a trade-off between performance and robustness has to be made. In this research, the game theory will be applied to optimize the trade-off.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.2
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• pp.60-65
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• 2012

This paper deals with an CAE analysis and optimization of injection molding for a mobile phone cover. Two design goals are established in the optimization; one is to switch over the feed system from cold runner to hot runner for the purpose of reducing material costs, and the other is to minimize the warpage in order to improve product quality. By the full-factorial experiments for design parameters, we showed that the cold runner design could be changed to the hot runner design by replacing the current resin with a new resin of higher fluidity. In addition, we could significantly reduce the warpage of the cover product under the hot runner system by optimizing packing pressure and packing time.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.65-73
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• 2015

This paper presents a method of predicting the machining parameters on the turning process of low carbon steel using a neural network with back propagation (BP) and particle swarm optimization (PSO). Cutting speed, feed rate, and depth of cut are used as input variables, while surface roughness and electric current consumption are used as output variables. The data from experiments are used to train the neural network that uses BP and PSO to update the weights in the neural network. After training, the neural network model is run using test data, and the results using BP and PSO are compared with each other.