• 대한기계학회논문집A
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• 제31권9호
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• pp.924-933
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• 2007

An impeller is a important part of turbo-machinery. It has a set of twisted surfaces because it consists of many blades. Five-axis machining is required to produce a impeller because of interference between tool and workpiece. It can obtain good surface integrity and high productivity. This paper proposes finish cutting method for machining impeller with 5-axis machining center and optimization of cutting condition by response surface method. Firstly, cutting methods are selected by consideration of operation characteristics. Secondly, response factors are determined as cutting time and cutting error for prediction of productivity. Experiments are projected by central composite design with axis point. Thirdly, regression linear models are estimated as single surface in the leading edge and as dual surface in the hub surface cutting. Finally, cutting conditions are optimized.

• Industrial Engineering and Management Systems
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• 제9권1호
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• pp.10-19
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• 2010

This paper presents an extended computing procedure for the global optimization of the triple response system (TRS) where the response functions are nonconvex (nonconcave) quadratics and the input factors satisfy a radial region of interest. The TRS arising from response surface modeling can be approximated using a nonlinear mathematical program involving one primary (objective) function and two secondary (constraints) functions. An optimization algorithm named triple response surface algorithm (TRSALG) is proposed to determine the global optimum for the nondegenerate TRS. In TRSALG, the Lagrange multipliers of target (secondary) functions are computed by using the Hooke-Jeeves search method, and the Lagrange multiplier of the radial constraint is located by using the trust region (TR) method at the same time. To ensure global optimality that can be attained by TRSALG, included is the means for detecting the degenerate case. In the field of numerical optimization, as the family of TR approach always exhibits excellent mathematical properties during optimization steps, thus the proposed algorithm can guarantee the global optimal solution where the optimality conditions are satisfied for the nondegenerate TRS. The computing procedure is illustrated in terms of examples found in the quality literature where the comparison results with a gradient-based method are used to calibrate TRSALG.

• 경영과학
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• 제29권3호
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• pp.81-89
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• 2012

Since introduced by Vining and Myers in 1990, the concept of dual response approach based on response surface methodology has widely been investigated and adopted for the purpose of robust design. Separately estimating mean and variance responses, dual response approach may take advantages of optimization modeling for finding optimum settings of input factors. Explicitly assuming functional relationship between responses and input factors, however, it may not work well enough especially when the behavior of responses are poorly represented. A sufficient number of experimentations are required to improve the precision of estimations. This study proposes an alternative to dual response approach in which additional experiments are not required. An artificial neural network has been applied to model relationships between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Training, validating, and testing a neural network with empirical process data, an artificial data based on the neural network may be generated and used to estimate response functions without performing real experimentations. A drug formulation example from pharmaceutical industry has been investigated to demonstrate the procedures and applicability of the proposed approach.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.294-297
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• 2004

Mean squared error (MSE) is an effective criterion to combine the mean and the standard deviation responses in dual response surface optimization. The bias and variance components of MSE need to be weighted properly in the given problem situation. This paper proposes a systematic method to determine the relative weights of bias and variance in accordance with a decision maker's prior and posterior preference structure.

• Korean Journal of Chemical Engineering
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• 제35권11호
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• pp.2241-2255
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• 2018

RSM methodology was applied to present mathematical models for the fabrication of polyvinylidene fluoride (PVDF) dual-layer hollow fibers in membrane distillation process. The design of experiments was used to investigate three main parameters in terms of polymer concentration in both outer and inner layers and the flow rate of dope solutions by the Box-Behnken method. According to obtained results, the optimization was done to present the proper membrane with desirable properties. The characteristics of the optimized membrane (named HF-O) suggested by the Box-Behnken (at the predicted point) showed that the proposed models are strongly valid. Then, a morphology study was done to modify the fiber by a combination of three types of a structure such as macro-void, sponge-like and sharp finger-like. It also improved the hydrophobicity of outer surface from 87 to $113^{\circ}$ and the mean pore size of the inner surface from 108.12 to 560.14 nm. The DCMD flux of modified fiber (named HF-M) enhanced 62% more than HF-O when it was fabricated by considering both of RSM and morphology study results. Finally, HF-M was conducted for long-term desalination process up to 100 hr and showed stable flux and wetting resistance during the test. These stepwise approaches are proposed to easily predict the main properties of PVDF dual-layer hollow fibers by valid models and to effectively modify its structure.

• 대한산업공학회지
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• 제39권5호
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• 한국기계가공학회지
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• 제16권3호
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• pp.30-37
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• 2017

When a wheel profile of a train-tram is designed, both train and tram tracks should be considered. This study designed a wheel profile that enables high-speed driving(200km/h) on the train track and low speed driving on the tram track with multiple sharp curves. The study used the approximation optimization method to reduce cost and time, used the sequential quadratic programming method as the optimized algorithm, and the central composite design and response surface method as an approximate model. The optimized wheel shape based on this approximation optimization method reduced wear of the initial wheel showed a better performance in terms of derailment and lateral force.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2006년 추계학술발표대회 개요집
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• pp.95-97
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• 2006

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.111-118
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• 2004

For the precise analysis of high velocity impact problem though FEM with element erosive method, the adequate mesh size and critical equivalent plastic strain(EQPS) is chosen prior to the simulation. In this research, it is strongly required from a standpoint that critical EQPS is used to decide whether perforation occurs or not. The optimization of dual armor plate consisting of 4340 steel and 2024 aluminium against a die steel sphere with high-velocity has been suggested using Lagrangian explicit time-integration code, NET2D. The response surface method based on the design of experiment is utilized for the size optimization. The optimized thickness of each layer, in which perforation does not occur, the strength of multi-layer is maximized and total weight is minimized, is obtained at a constant velocity of a pellet with a designated total thickness.

• International Journal of Precision Engineering and Manufacturing
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• 제9권4호
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• pp.51-56
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• 2008

Thermoforming is one of the most versatile and economical processes available for shaping polymer products, but obtaining a uniform thickness of the final product using this method is difficult. Heater power adjustment is very important because the thickness distribution depends strongly on the distribution of the sheet temperature. In this paper, the steady-state optimum distribution of heater power is first ascertained by a numerical optimization to obtain a uniform sheet temperature. The time-dependent optimal heater input is then determined to decrease the temperature difference through the direction of the thickness using the response surface method and the D-optimal method. The optimal results show that the time-dependent optimum heater power distribution gives an acceptable uniform sheet temperature in the forming temperature range by the end of the heating process.