• Journal of Korea Water Resources Association
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• v.38 no.5 s.154
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• pp.415-425
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• 2005

This study estimated the optimal rain gauge density and sub-basin size for the application of a daily rainfall-runoff analysis model called SWAT (Soil and Water Assessment Tool). Simulated rainfall data using a WGR multi-dimensional precipitation model (Waymire et al., 1984) were applied to SWAT for runoff estimation, and then the runoff error was analyzed with respect to various rain gauge density and sub-basin size. As results of the study, we could find that the optimal sub-basin size and the representative area of one rain gauge are similar to be about $80km^2$ for the Yong-Dam dam basin.

• Journal of Korean Society for Quality Management
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• v.18 no.2
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• pp.93-99
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• 1990

This paper considers the selection of process plans for a flexible manufacturing machine. Most of the planning models for the automated manufacturing systems are based on the assumption that for each part there is only one process plan available. This paper considers that for each part a number of different process plans are available, each of which may require specific types of tools. If the requisite tools are not on the machine, one or more tool switches must occur before the process plan can be processed. This paper develops an optimal algorithm of branch and bound method for the selection of process plans to minimize the number of tool switches.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.3
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• pp.109-114
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• 2016

This study presents the optimal hardness range for a coated layer of a workpiece when the diamond tool cuts the corner-cube pattern on the coated plates using an ultra-precision diamond-turning machine. Two kinds of coated plates, which have the hardness range of 211~328 Vickers hardness, are used on the first experiments. The form accuracy for the corner-cube pattern could be achieved through the following experiments using the accumulated thin copper plates in second experiments, having optimal 265~275 Vickers hardness based on the basic first experiments without tool wear. When the number of machining adjustments was increased to seven times, having machining depth was reduced successively in second experiment, a fine surface could be achieved without tool wear.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.83-93
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• 2007

This paper gives an attempt to build a decision support tool linked with a simulation software called ARENA for evaluating and comparing the performance of the push and pull material driven strategies operating in the flow shop environment with a bottleneck resource as the shop's constraint. To be fair for such evaluation, the comparison must be made fairly under the optimal setting of both systems' operating parameters. In this study, an optimal-seeking heuristic algorithm, Genetic Algorithm (GA), is employed to suggest a systems' best design based on the economic consideration, which is the profit generated from the system. Results from the study have revealed interesting outcomes, letting us know the strength and weakness of the push and pull mechanisms as well as the effect of each operating parameter to the overall system's financial performance.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.83-88
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• 2001

In order to suggest the proper optimal conditions of the CNC milling machining for the Thin-wall surface, some experiments were carried out. The process was applied in the aerospace industry for the machining of light alloys, notably aluminium. In recent year, however, the mold and die industry has begun to use the technology for the production of components, including those manufactured from hardened tool steels. And the end mill is an important tool in the milling process. A typical example for the end mill is the milling of pocket and slot in which a lot of material is removed from the workpiece. Therefore the proper selection of cutting parameter for end milling is one of the important factors affecting the cutting cost. In this paper, we choose the optimal parameters(cutting forces) to cut thin-walled Al part by experiment.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.2
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• pp.165-170
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• 2000

In order to perform a successful material cutting process, the operators are to select the suitable machining tools and cutting conditions for the cutting environment. Up to now, this has been a complicated procedure done by the data in the tool manufacturers' paper catalog and the operator's experiencial knowledge, so called heuristics. This research is motivated by the fact that using computer techniques in processing vast amount of data and information, the operator can determine the tool and cutting condition easily. In the developed program, the selection of milling cutter, insert, and components are combined to provide optimal cutting speed, depth of cut, feed rate, rpm, and power. This program also provides the selection routine for end mill, drilling, turning, and grinding where the suitable tools are selected by workpiece, holder type, cut type, and insert shape.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.429-434
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• 2005

In this paper sandwich structures like beams and plates are optimised by using parametric study. The structures are composed of fibre reinforced composites for facial material and resin concrete and PVC foam for core materials. The stacking sequences and thickness of the composites are controlled as major parameters to find out the optimal condition for machine tool components. For the plate structure for machine tool bed composites-skined sandwich structure which has several ribs are proposed to enhance both directional bending stiffnesses at the same time. From the results optimal configuration and materials for high precesion machine tools are proposed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.278-283
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• 1997

This paper proposes a systematic design method for axial(or thrust) magnetic bearings using optimal design methodology. The objective of the optimal design is to minimize bearing volume. The constraints include the bearing load capacity, linearized bearing stiffness and damping, the magnetic flux density, and geometric relations. In order to obtain design values which can be applied to fabrication of bearings, branch and bound method was introduced in the postprocessing procedure of optimal design results. Verification of the proposed design methodology was perfomed by an example.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.03b
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• pp.77-81
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• 1999

The predictions of metal flow forging load optimal die angle and preform size are not so easy in turbine blade forging. First of all the quality of final product is influenced by side force which is one of the significant factors. in this study slab method is applied to determine optimal die angle minimizing side force and the position of preform Finally drawing of die design is obtained in optimal die angle with developing tool that is composed of Visual Basic.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.188-194
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• 2015

This paper proposes a generalized regression neural network (GRNN) based algorithm for data interpolation and design optimization of brushless dc (BLDC) motor. The procedure makes use of magnet length, stator slot opening and air gap length as design variables. Cogging torque and average torque are treated as performance indices. The optimal design necessitates mitigating the cogging torque and maximizing the average torque by varying design variables. The data set for interpolation and ensuing design optimisation using GRNN is obtained by modeling a standard BLDC motor using finite element analysis (FEA) tool MagNet 7.1.1. The performance indices of the standard motor obtained using FEA are validated with an experimental model and an analytical method. The optimal design is authenticated using particle swarm optimization (PSO) algorithm and the performance indices of the optimal design obtained using GRNN is validated using FEA. The results indicate the suitability of GRNN as an interpolation and design optimization tool for a BLDC motor.