• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.4
• /
• pp.856-865
• /
• 1994

Cylindrical fine-ceramics, $Al_{2}O_{3}$, was lapped on its outer surface by vibrational lapping unit manufactured in the laboratory. Cylindrical lapping of fine-ceramics is necessarily be characterized and optimized because its process as other finishing methods is time-spending and, so, inefficient one, and because it is very complicated and random process affected by numerous factors in itself and in its environment. In this study, an efficient experimental approach, experimental design method, was used to analyze characteristics of the cylindrical lapping of fine-ceramics, $Al_{2}O_{3}$, and response surface methodology(RSM) to find out the optimal variables combination for the maximum improvement of surface roughness($R_a$). From the final surface roughness point of view in the given lapping conditions, a stationary point or optimal lapping conditions as well as the possible maximum improvement of surface roughness($R_a$) was predicted.

• Food Engineering Progress
• /
• v.15 no.2
• /
• pp.97-115
• /
• 2011

A review about the application of response surface methodology in the optimization of food technology is presented. The theoretical principles of response surface methodology and steps for its application are described. The response surface methodologies : three-level full factorial, central composite, Box-Behnken, and Doehlert designs are compared in terms of characteristics and efficiency. Furthermore, recent references of their uses in food technology are presented. A comparison between the response surface designs (three-level full factorial, central composite, Box-Behnken and Doehlert design) has demonstrated that the Box-Behnken and Doehlert designs are slightly more efficient than the central composite design but much more efficient than the three-level full factorial designs.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2005.11a
• /
• pp.211-214
• /
• 2005

This research studied robust design of composite structure under combined loading of bending and torsion. DOE (Design of Experiment) technique was used to find important design factors. The results show that the beam height, beam width, layer thickness and stack angle of outer-layer are important design parameter. The $2^{nd}$ DOE and RSM (Response Surface Model) were conducted to obtain optimum design. Multi-island genetic algorithm was used to optimum design. An approximate value of 6.65 mm in deflection was expected under optimum condition. Six sigma robust design was conducted to find out guideline for control range of design parameter. To acquire six sigma level reliability, the sigma level reliability, the standard deviation of design parameter should be controlled within 2.5 % of average design value.

• Korean Management Science Review
• /
• v.29 no.3
• /
• pp.81-89
• /
• 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.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.557-564
• /
• 2006

Life-cycle performance and maintaining cost predictions are required for the effective management for bridges. In Korea, the importance of management of bridges has been recognized over the past two decades, resulting in the development of databases and various bridge management support tools by both government and private sectors. However, none of these tools has truly included the expected features of the bridge management system (EMS) for the next generation such as the quantification of the effects of maintenance interventions on bridge condition and safety. In this paper, a novel quantification process to simulate the life-cycle performance of steel box bridges has been developed. The process is based on the Response Surface method. Various performance-related variables aloe investigated to identify a set of significant design variables to construct the response surfaces.

• Environmental Engineering Research
• /
• v.15 no.2
• /
• pp.63-70
• /
• 2010

In this study, the response surface method and experimental design were applied as an alternative to conventional methods for the optimization of coagulation tests. A central composite design, with 4 axial points, 4 factorial points and 5 replicates at the center point were used to build a model for predicting and optimizing the coagulation process. Mathematical model equations were derived by computer simulation programming with a least squares method using the Minitab 15 software. In these equations, the removal efficiencies of turbidity and total organic carbon (TOC) were expressed as second-order functions of two factors, such as alum dose and coagulation pH. Statistical checks (ANOVA table, $R^2$ and $R^2_{adj}$ value, model lack of fit test, and p value) indicated that the model was adequate for representing the experimental data. The p values showed that the quadratic effects of alum dose and coagulation pH were highly significant. In other words, these two factors had an important impact on the turbidity and TOC of treated water. To gain a better understanding of the two variables for optimal coagulation performance, the model was presented as both 3-D response surface and 2-D contour graphs. As a compromise for the simultaneously removal of maximum amounts of 92.5% turbidity and 39.5% TOC, the optimum conditions were found with 44 mg/L alum at pH 7.6. The predicted response from the model showed close agreement with the experimental data ($R^2$ values of 90.63% and 91.43% for turbidity removal and TOC removal, respectively), which demonstrates the effectiveness of this approach in achieving good predictions, while minimizing the number of experiments required.

• Journal of Mechanical Science and Technology
• /
• v.20 no.1
• /
• pp.133-146
• /
• 2006

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.12 no.6
• /
• pp.461-468
• /
• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.28 no.7
• /
• pp.879-886
• /
• 2004

A numerical optimization has been carried out to determine the shape of the three-dimensional channel with oblique ribs attached on both walls to enhance turbulent heat transfer. The response surface based optimization is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid flow and heat transfer. Shear stress transport (SST) turbulence model is used as a turbulence closure. Numerical results fur heat transfer rate show good agreements with experimental data. four dimensionless variables such as, rib pitch-to-rib height ratio, rib height-to-channel height ratio, streamwise rib distance on opposite wall to rib pitch ratio, and the attack angle of the rib are chosen as design variables. The objective function is defined as a linear combination of heat-transfer and friction-loss related coefficients with a weighting factor. D-optimal method is used to determine the training points as a means of design of experiment. Sensitivity of the objective parameters to each design variable has been analyzed. And, optimal values of the design variables have been obtained in a range of the weighting factor.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.2
• /
• pp.14-21
• /
• 2019

In recent years, the use of composite structures has become commonplace in various fields such as aerospace, architecture, and civil engineering. In this study, A method is proposed to find optimal position of bolt hole for fastening of composite structure. In the case of composites, stress distribution is very complicated, and design optimization based on this phenomenon increases difficulty. In selecting the optimum position of the bolt hole, the response surface method(rsm), which is a method of optimization, was applied. A response surface was created based on design points by multiple finite element analyzes. The position of the bolt hole that minimizes the stress when bolting on the response surface was found. The distribution of the stress at the position of the optimal hole was much lower than that of the initial design. Based on the results of this study, it is possible to increase the design safety factor of the structure by appropriately selecting the position of the bolt hole according to various load types when designing the structure and civil structure.