• Korean Chemical Engineering Research
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• v.46 no.5
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• pp.903-914
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• 2008

This study was undertaken for the production capacity expansion and energy saving through entire process simulation and optimization for the commercial process of manufacturing monoethylene glycol as a staple from ethylene oxide. Aspen $Plus^{TM}$(ver. 2006) was employed in the simulation and optimization work. The multicomponent vapor-liquid equilibria involved in the process were calculated using the NRTL-RK equation. As for the binary interaction parameters required for a total of 91 binary systems, those for 8 systems were self-supplied by the simulator, those for 28 systems were estimated through regression of the VLE data in the literature, and the remainder were estimated with the estimation system built in the simulator. Subsequent to ascertaining the accuracy of the generated parameters through comparison between actual and simulated process data, sensitive variables highly affecting the process were searched and selected using sensitivity analysis tool in the simulator. The optimum operating conditions minimizing the total heat duty of the process were investigated using the optimization tool based on the successive quadratic programming in the simulator.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.51-58
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• 2004

Optimization of engine desist and operation parameters using a genetic algorithm was demonstrated for direct injection diesel engine combustion. A micro genetic algorithm and a modified KIVA-3V code were used for the analysis and optimization of the engine combustion. At each generation of the optimization step the micro genetic algorithm generated five groups of parameter sets, and the five cases of KIVA-3V analysis were to be performed either in series or in parallel. The micro genetic algorithm code was also parallelized by using MPI programming, and a multi-CPU parallel supercomputer was used to speed up the optimization process by four times. An example case for a fixed engine speed was performed with six parameters of intake swirl ratio, compression ratio, fuel injection included angle, injector hole number, SOI, and injection duration. A simultaneous optimization technique for the whole range of engine speeds would be suggested for further studies.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.5
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• pp.499-505
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• 2003

In the design of mobile wireless communication system, base station location is one of 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 fur 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.66-72
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• 2011

Injection pressure is an important factor in filling procedure for injection molded parts. In addition, weldlines should be avoided to successfully produce injection molded parts. In this study, we optimally obtained injection molding process parameters that minimize injection pressure. Then, we determined the thickness of the part to avoid weldlines. To solve the optimization problem proposed, we employed MAPS-3D (Mold Analysis and Plastics Solution-3 Dimension), a commercial CAE tool for injection molding analysis, and PIAnO (Process Integration, Automation, and Optimization) as a commercial PIDO (Process Integration and Design Optimization) tool. We integrated MAPS-3D into PIAnO, automated the analysis and design procedure, and performed optimization by employing PQRSM (Progressive Quadratic Response Surface Method) equipped in PIAnO. We successfully obtained optimization results, which demonstrates the effectiveness of our design method.

• Transactions of Materials Processing
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• v.15 no.4 s.85
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• pp.295-303
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• 2006

Optimization is carried out to determine process parameters which reduce the amount of springback and improve shape accuracy of a deep drawn product in sheet metal forming process. The study uses the amount of stress deviation along the thickness direction in the deep drawn product as an indicator of springback instead of springback simulation. The scheme incorporates with an explicit elasto-plastic finite element method for calculation of the final shape and the stress deviation The optimization method adopts the response surface method in order to seek for the optimum condition of process parameters such as the blank holding force and the draw-bead force. The present scheme is applied to design of the variable blank holding force in an U-draw bending process and the application is further extend ε d to the design of draw-bead force in a front side member formed with advanced high strength steel (AHSS) sheets of DP60. Results show that design of process parameter is well performed to decrease the stress deviation through the thickness and to reduce the amount of springback. The present analysis provides a guideline in a design stage for controlling the springback based on the finite element simulation of the complicated parts.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.11
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• pp.1100-1107
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• 2007

In this study, a method to characterize material properties of adhesive that is used in a layered plates bonding process is developed by combined evaluation of experiment, simulation and optimization technique. A small bonded specimens of rectangular plate are prepared to this end, and put into a thermal loading conditions. $Moir{\acute{e}}$ interferomety is used to measure submicron displacements occurred during the process. The elevated temperature is chosen as control factors. FE analysis with constant values for the adhesive materials is also carried out to simulate the experiment. Significant differences are observed from the two results, in which the simulation predicts the monotonic increase of the bending displacement whereas the measurement shows decrease of the displacement at above $75^{\circ}C$. In order to minimize the difference of the two, material parameters of the adhesive at a number of different temperatures are posed as unknowns to be determined, and optimization is conducted. As a result, optimum material parameters are found that excellently matches the simulation and experiment, which are decreased with respect to the temperature.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1101-1106
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• 2005

The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Operating data (trace parameters) were collected on-line but quality data (measurement parameters) were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Thus, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were employed for data generation, and then modeling was accomplished, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to the control parameters. The dynamic polynomial neural network (DPNN) was used for data modeling that used the ingot fabrication data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.43-52
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• 2022

Design of a controller for a high-precision servo control system has been a popular topic while finding optimal parameters for multiple controllers is still a challenging subject. In this paper, we propose a practical scheme to optimize multi-parameters for the robust servo controller design by introducing a new cost function and optimization scheme. The proposed design method provides a simple and practical tool for the systematic servo design to reduce the control error with guaranteeing robust stability of the overall system. The reduction of the position error by 24% along with a faster convergence rate is demonstrated using a typical hard disk drive servo controller with 41 parameters.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1611-1616
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• 2004

The objective of this study is to simulate the etching characteristics under different process parameters for the optimization of etching process. The etching characteristics such as the etching factor were investigated under different operating conditions and compared with the spray characteristics. The spray characteristics were measured by using Phase Doppler Anemometer. The correlation between the etching characteristics and the spray characteristics was analyzed to simulate the etching characteristics under the actual parameters of the etching process. The parameters were distance of nozzle tip and pipe pitch. To improve the uniformity and value of etching factor in the etching process, the process parameters should be designed optimally. The distribution of spray was simulated by the Monte-Carlo Method and the process parameters were optimized by the design of experiments(DOE).

• Bulletin of the Korean Mathematical Society
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• v.34 no.4
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• pp.495-508
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• 1997

The problem of optimization in choosing of evasion parameters in differential games is considered. Existence of optimal parameters is proved and algorithm of their is shown. The example is cited. This work adjoins investigations [1-11].