• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.568-573
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• 1996

In this paper, A design strategy of the Surface Mounting Device for accurate and better performance is studied. Analytical Modeling. Sensitivity analysis and optimization are being conducted. The ANSYS software and experimental method are used for verification of the analytical equations withboundary conditons. Through the sensitivity analysis, the most dominant design parameters can be detected. The optimum design parameters for performing given performing given perfomances are selected by using the optimization algorithm. The design tool based on the design strategy for the analysis, modeling and optimization will be useful for a re-design and better perofrmance of the SMD.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.120-128
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• 1997

In this paper, A design strategy of the Surface Mounting Device for accurate and better performance is studied. Analytical modeling, sensitivity analysis, and optimization are being conducted. The ANSYS software and experimental method are used for the verification of the analytical equations with boundary conditions. Through the sensitivity analysis, the most dominant design parameter can be detected. The optimum design parameters for improving the given performances are selected by using the optimiza- tion algorithm. The design tool based on the design strategy for the analysis, modeling, and optimization will be useful for are-design and better improving of the SMD.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.263-277
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• 2024

Artificial Neural Networks (ANNs) are artificial learning algorithms that provide successful results in solving many machine learning problems such as classification, prediction, object detection, object segmentation, image and video classification. There is an increasing number of studies that use ANNs as a prediction tool in soil classification. The aim of this research was to understand the role of hyperparameter optimization in enhancing the accuracy of ANNs for soil type classification. The research results has shown that the hyperparameter optimization and hyperparamter optimized ANNs can be utilized as an efficient mechanism for increasing the estimation accuracy for this problem. It is observed that the developed hyperparameter tool (HyperNetExplorer) that is utilizing the Covariance Matrix Adaptation Evolution Strategy (CMAES), Genetic Algorithm (GA) and Jaya Algorithm (JA) optimization techniques can be successfully used for the discovery of hyperparameter optimized ANNs, which can accomplish soil classification with 100% accuracy.

• Korean Journal of Computational Design and Engineering
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• v.6 no.3
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• pp.169-173
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• 2001

Presented in this paper is a CPO tool-path linking procedure optimizing technological objectives, such as dealing with islands (positive and negative) and minimizing tool retractions, drilling holes and slotting. Main features of the proposed algorithm are as follows; 1) a data structure, called a 'TPE-net', is devised to provide information on the parent/child relationships among the tool-path-elements, 2) the number of tool retractions is minimized by a 'tool-path-element linking algorithm'fading a tour through the TPE-net, and 3) the number of drilling holes is minimized by making use of the concept of the 'free space'.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.1
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• pp.48-56
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• 2009

This paper presents the results of miniaturized micro milling machine tool development for micro precision machining process. Finite element analysis has been performed to know the relationship between design dimensional variables and structural stiffness in terms of static, dynamic, thermal aspects. Design optimization has been performed to optimize the design variables of micro machine tool to minimize the volume, weight and deformation of machine tool structure and to maximize the stiffness in terms of static, dynamic, and thermal characteristics. This study presents the assessment of the technology incentive for the minimization of machine tool in the quantitative context of static, dynamic stiffness, thermal resistance and thus the accuracy implications. This study can also be provided a basic knowledge for further research of micro factory development.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.100-105
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• 2003

With the recent development of machining technology, high speed machining process is widely used for-the mold and difficult-to -cut-materials machining since it allows achieving high productivity and surface quality. However, during the high speed machining process, high cutting speed and feed rate can cause abrupt tool life decrease due to rapid rising of the cutting tool temperature. Such situation may cause increase of machining cost. Thus, in this study, developed optimization algorithm is applied to determine optimal machining variables for multiple high speed machining. The R-T characteristic curve for machining economics problems with a linear-lorarithmic tool life model is determined by applying sensitivity analysis. finally, a series of high speed machining experiments are performed to determine the desired optimal machining variables, and the results are analyzed.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.3
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• pp.310-315
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• 2011

General portal machine represents a distinct weak spot concerning their structural behavior because of long protruding structure components, such as saddles and rams. The weak point causes the deformation of the machine tool and consequently rises a severe machining error. The purpose of this study is to improve the structural design of crossrail in order to minimize it's distortion. Tool Center Point (TCP) was chosen as a reference point for evaluating the distortion effect of a crossrail and topological optimization was adopted as a method of structural design improvement. The displacements of TCP according to the machining positions were investigated by structural analyses for both of original crossrail design and the improved one. The comparing results showed that the displacement of TCP could be reduced about 55% maximum.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.12
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• pp.693-699
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• 2013

This paper describes a method for size optimization of the major design variables for solar water heating systems at the stage of concept design. The widely used RETScreen simulation tool was used for optimization. Currently, the RETScreen tool itself does not provide a function for optimization of the design parameters. In this study, an optimizer was combined with the software. A comparative study was performed to evaluate the RETScreen-based approach with the case study of a solar heating system in an office building. The optimized results using the RETScreen model were compared to previously published results with the TRNSYS model. The objective function of the optimization is the life-cycle cost of the system. The optimized design results from the RETScreen model showed good agreement with the optimized TRNSYS results for the solar collector area and storage volume, but presented a slight difference for the collector slope angle in terms of the converged direction of the solutions. The energy cost, life-cycle cost, and thermal performance regarding collector efficiency, system efficiency, and solar fraction were compared as well, and the RETScreen model showed good agreement with the TRNSYS model for the conditions of the base case and optimized design.

• Structural Engineering and Mechanics
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• v.77 no.3
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• pp.417-439
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• 2021

The geometric nonlinearity has been successfully integrated with the design of steel structural system. Thus, the tubular lattice girder, one application of steel structural systems have already been optimized to obtain an economic design following the completion of computationally expensive design procedure. In order to decrease its computing cost, this study proposes to employ five multi-objective metaheuristics for the design optimization of geometrically nonlinear tubular lattice girder. Then, the employed multi-objective optimization algorithms (MOAs), NSGAII, PESAII, SPEAII, AbYSS and MoCell are evaluated considering their computing performances. For an unbiased evaluation of their computing performance, a tubular lattice girder with varying size-shape-topology and a benchmark truss design with 17 members are not only optimized considering the geometrically nonlinear behavior, but three benchmark mathematical functions along with the four benchmark linear design problems are also included for the comparison purpose. The proposed experimental study is carried out by use of an intelligent optimization tool named JMetal v5.10. According to the quantitative results of employed quality indicators with respect to a statistical analysis test, MoCell is resulted with an achievement of showing better computing performance compared to other four MOAs. Consequently, MoCell is suggested as an optimization tool for the design of geometrically nonlinear tubular lattice girder than the other employed MOAs.

• Transactions of Materials Processing
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• v.3 no.2
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• pp.147-155
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• 1994

The service life of tools in metal forming technology is to a large extent limited by wear and fatigue fracture of the active elements. This presents a basic request for tool cost minimization and reduction of extensive machine down time, caused by premature tool failure. Currents developments are dominated by steps to reduce the causes of tool failure. A main problem of forming technology remains the insufficient reliability of tools due to a large and incalculable life time fluctuation. Only a systematic investigation of the failure mechanisms and operational loading of tools can lead to future improvements in tool layout, that is optimization of tool usage.