• 한국기계가공학회지
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• 제14권6호
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• pp.90-97
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• 2015

Optimization of multi-quality characteristics in injection molded parts is very important, but it is sometimes difficult for part/mold designers. The objective of this study is to develop a practical design methodology for optimizing two-quality characteristics of injection molded parts. To attain this end, we developed a new design-range reduction algorithm based on Taguchi's orthogonal arrays for two characteristics. Then, the algorithm was integrated with commercial injection-molding simulation tools. A feature of the proposed methodology is that it allows field-designers unfamiliar with general optimization methods to be able to apply the methodology to their design problems with ease. Finally, we have applied the proposed design methodology to optimization of weldlines and deflections in an actual bezel model. The results show the usefulness of this methodology.

• Journal of Electrical Engineering and Technology
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• 제6권4호
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• pp.513-518
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• 2011

In this paper, a unified design environment is developed for the optimization of electric machines based on continuum sensitivity. For electromagnetic (EM) system analysis, COMSOL scripting environment is used. Optimization module is developed by MATLAB programming, which can be combined with COMSOL script commands. The modules are combined into one MATLAB project, and iteration process necessary for the optimization of EM system can be performed efficiently. During the design process, visual feedback of the current design status is given to the designer. In addition, the B-Spline parametrization of the nodal points is implemented to obtain smooth boundary of the device. The developed software is applied to the problem of finding uniform flux density distribution at the air gap of an electromagnet to verify its feasibility and effectiveness.

• 한국기계가공학회지
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• 제9권6호
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• pp.21-28
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• 2010

This study shows an optimization procedure for an automatic determination on the gate position to ensure the fill-uniformity within a part cavity by using the injection molding simulation. For an optimization, the maximum pressure-difference within a part cavity induced at the stage of filling is used to evaluate degree of fill-uniformity. In addition, a direct search scheme based on the reduction of design space is developed and applied in the optimization problem. This corresponding proposed methodology was applied in the optimization on the gate location for a CD-tray molding, as a result, showed the improvement of the fill-uniformity within the cavity.

• Journal of Microbiology and Biotechnology
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• 제21권12호
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• pp.1250-1256
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• 2011

In this study, Bacillus licheniformis cells were immobilized by entrapment in calcium alginate beads and were used for production of alkaline protease by repeated batch process. In order to increase the stability of the beads, the immobilization procedure was optimized by statistical full factorial method, by which three factors including alginate type, calcium chloride concentration, and agitation speed were studied. Optimization of the enzyme production medium, by the Taguchi method, was also studied. The obtained results showed that optimization of the cell immobilization procedure and medium constituents significantly enhanced the production of alkaline protease. In comparison with the free-cell culture in pre-optimized medium, about 7.3-fold higher productivity was resulted after optimization of the overall procedure. Repeated batch mode of operation, using optimized conditions, resulted in continuous production of the alkaline protease for 13 batches in 19 days.

• International Journal of Contents
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• 제12권3호
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• pp.22-28
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• 2016

Tensor with missing or incomplete values is a ubiquitous problem in various fields such as biomedical signal processing, image processing, and social network analysis. In this paper, we considered how to reconstruct a dataset with missing values by using tensor form which is called tensor completion process. We applied Tucker factorization to solve tensor completion which was built base on optimization problem. We formulated the optimization objective function using components of Tucker model after decomposing. The weighted least square matric contained only known values of the tensor with low rank in its modes. A first order optimization method, namely Nonlinear Conjugated Gradient, was applied to solve the optimization problem. We demonstrated the effectiveness of the proposed method in EEG signals with about 70% missing entries compared to other algorithms. The relative error was proposed to compare the difference between original tensor and the process output.

• 한국기계가공학회지
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• 제14권3호
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• pp.85-91
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• 2015

The press-fit shaft is an important part used in automobiles, vessels, and trains. This study proposes an optimized design method to reduce damage that may occur in the press-fitted shaft by modifying the shape of the boss step of the press-fitted shaft. To reduce the time and cost of running the optimized design method, an approximate design optimization is applied and an optimized algorithm is generated using a genetic algorithm that is widely used in engineering fields and an approximate model using a response surface method. The planned experiments for the data that are needed to generate the approximate model use a central composite design (CCD) and Latin hypercube sampling (LHS), and the results of the approximate optimization using the above two design of experiments are to be compared.

• 대한기계학회논문집A
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• 제30권6호
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• pp.722-727
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• 2006

Bone fracture healing is one of the important topics in biomechanics, demanding computation simulations due to the difficulty of obtaining experimental or clinical results. In this study, we adopt the design space optimization method which was established by the authors as a tool for the simulation of bone growth using its evolutionary characteristics. As the mechanical stimulus, strain energy density is used. We assume that bone tissues over a threshold strain energy density will be differentiated and bone tissues below another threshold will be resorbed. Under compression and torsion as loadings, the filling process of the defect is well illustrated following the given mechanical criterion. It is shown that the design space optimization is an excellent tool for simulating the evolutionary process of bone growth, which has not been possible otherwise.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1132-1142
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• 2001

The paper describes the construction of global function approximation models for use in design optimization via global search techniques such as genetic algorithms. Two different approximation methods referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the training data is not sufficiently provided or uncertain information may be included in design process. Fuzzy inference system is the central system for of identifying the input/output relationship in both methods. The paper introduces the general procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and presents their generalization capabilities in terms of a number of fuzzy rules and training data with application to a three-bar truss optimization.

• 한국공작기계학회논문집
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• 제16권5호
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• pp.205-210
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• 2007

The integration method of binary and real encoding in genetic algorithm is proposed to deal with design variables of various types in gear drive design. The method is applied to optimum design of multi-stage gear drive. Integer and Discrete type design variables represent the number of teeth and module, and continuous type design variables represent face width, helix angle and addendum modification factor etc. The proposed genetic algorithm is applied for the gear ratio optimization and the volume optimization(minimization) of multi-stage geared motor which is used in field. In result, the proposed design optimization method shows an effectiveness in optimum design process and the new design has a better results compared with the existing design.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1063-1068
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• 2008

A lens system of a camera module for mobile phones is comprised of the composition and design of various shapes of lens. To improve responses such as the modular transfer function (MTF), a lens system should always be constructed by considering uncertainty that can be caused by manufacturing and assembly error. In this study, tolerance optimization using the Latin Hypercube Sampling (LHS) technique is performed. In order to reduce the computational burden of the tolerance optimization process and decrease the influence from numerical noise effectively, we use the Progressive Quadratic Response Surface Modeling (PQRSM), which is one of Sequential Approximate Optimization (SAO) techniques. Using this method, we achieved optimal tolerance for each lens and obtained reliability for satisfying user‘s requirements. In addition, through the design process the manufacturing and assembly cost of a lens system was reduced.