• 대한기계학회:학술대회논문집
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• 대한기계학회 2005년도 창립60주년 기념 추계 학술대회
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• pp.172.2-172.2
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• 2005

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.803-804
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• 2013

• 한국공작기계학회논문집
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• 제16권3호
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• pp.8-14
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• 2007

The geometry in the weight reduction design is very required to be started from the conceptual design with low cost, high performance and quality. In this point, a topological shape fur optimization concerned with conceptual design of structure is important. The method used in this paper combines three optimization techniques, where the shape and physical dimensions of the structure and material distribution are hierachically optimized, with the maximum rigidity of structure and lightweight. As the applications, the technology of weight reduction design is applied on designs of aluminum control arm and inner panel of hood.

• 한국항해항만학회지
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• 제30권2호
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• pp.137-143
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• 2006

The optimum grillage design belongs to nonlinear constrained optimization problem. The determination of beam scantlings for the grillage structure is a very crucial matter out of whole structural design process. The performance of optimization methods, based on penalty functions, is highly problem-dependent and many methods require additional tuning of some variables. This additional tuning is the influences of penalty coefficient, which depend strongly on the degree of constraint violation. Moreover, Binary-coded Genetic Algorithm (BGA) meets certain difficulties when dealing with continuous and/or discrete search spaces with large dimensions. With the above reasons, Real-coded Micro-Genetic Algorithm ($R{\mu}GA$) is proposed to find the optimum beam scantlings of the grillage structure without handling any of penalty functions. $R{\mu}GA$ can help in avoiding the premature convergence and search for global solution-spaces, because of its wide spread applicability, global perspective and inherent parallelism. Direct stiffness method is used as a numerical tool for the grillage analysis. In optimization study to find minimum weight, sensitivity study is carried out with varying beam configurations. From the simulation results, it has been concluded that the proposed $R{\mu}GA$ is an effective optimization tool for solving continuous and/or discrete nonlinear real-world optimization problems.

• Journal of Welding and Joining
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• 제34권3호
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• pp.23-30
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• 2016

This paper discusses the optimization of friction stir spot welding (FSSW) process parameters for joining Aluminum alloy (AA6061-T6) with Magnesium alloy (AZ31B) sheets. Prior to optimization an empirical relationship was developed to predict the Tensile Shear Fracture Load (TSFL) incorporating the four most important FSSW parameters, i.e., tool rotational speed, plunge rate, dwell time and tool diameter ratio, using response surface methodology (RSM). The experiments were conducted based on four factor, five levels central composite rotatable design (CCD) matrix. The maximum TSFL obtained was 3.61kN, with the tool rotation of 1000 rpm, plunge rate of 16 mm/min, dwell time of 5 sec and tool diameter ratio of 2.5.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2001년도 가을 학술발표회 논문집
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• pp.183-190
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• 2001

Topology optimization. has been evolved into a very efficient conceptual design tool and has been utilized into design engineering processes in many industrial parts. In recent years, topology optimization has become the focus of structural optimization design and has been researched and widely applied both in academy and industry. Traditional topology optimization has been using homogenization method and optimality criteria method. Homogenization method provides relationship equation between structure which includes many holes and stiffness matrix in FEM. Optimality criteria method is used to update design variables while maintaining that volume fraction is uniform. Traditional topology optimization has advantage of good convergence but has disadvantage of too much convergency time and additive checkerboard prevention algorithm is needed. In one way to solve this problem, element remove method is presented. Then, it is applied to many examples. From the results, it is verified that the time of convergence is very improved and optimal designed results is obtained very similar to the results of traditional topology using 8 nodes per element.

• 소성∙가공
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• 제30권3호
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• pp.125-133
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• 2021

In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process

• 대한기계학회논문집A
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• 제35권2호
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• pp.183-190
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• 2011

최근 이동통신 가입자의 증가로 인해 기지국의 수요도 증가하게 되었다. 하지만 기지국 설치 장소의 부족으로 인해 이동통신모듈의 크기가 소형화 되어야 할 필요성이 생겼다. 이동통신모듈의 소형화를 위해서는 모듈 겉면에 부착된 히트싱크의 크기가 소형화 되어야 한다. 또한 모듈의 열적 안정성을 보장하기 위해 설치된 전자부품의 온도가 허용온도보다 낮아야 한다. 이를 위해 상용 PIDO(Process Integration and Design Optimization) 툴인 PIAnO와 전산유체역학 프로그램인 FLOTHERM을 사용하여 전자부품의 온도를 허용온도보다 낮게 유지시키면서 히트싱크의 부피를 최소화하였다. 그 결과, 이동통신 모듈에 설치된 전자부품의 허용온도를 만족하면서 모듈의 부피를 41.9% 감소시킬 수 있었다.

• 한국생산제조학회지
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• 제18권4호
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• pp.430-435
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• 2009

The cooling stage greatly affects the product quality in the injection molding process. The cooling system that minimizes temperature variance in the product surface will improve the quality and the productivity of products. The cooling circuit optimization problem that was once solved by a response surface method with 4 design variables. It took too much time for the optimization as an industrial design tool. It is desirable to reduce the optimization time. Therefore, we tried the back-propagation algorithm of artificial neural network(BPN) to find an optimum solution in the cooling circuit design in this research. We tried various ways to select training points for the BPN. The same optimum solution was obtained by applying the BPN with reduced number of training points by the fractional factorial design.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1980-1983
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• 2005

The characteristic of sheet metal process is the few loss of material during process, the short processing time and the excellent price and strength. The sheet metal process with above characteristic is common used in industrial field, but in order to analysis irregular field problems the reliable and economical analysis method is demanded. Finite element method is very effective method to simulate the forming processes with good prediction of the deformation behaviour. Among Finite element method, The static-implicit finite element method is applied effectively to analyze real-size auto-body panel stamping processes, which include the forming stage. In this paper, it was focussed on the drawability factors on auto-body panel stamping by AUTOFORM with using tool planing alloy to reduce law price as well as high precision from Design Optimization of ide. According to this study, the results of simulation will give engineers good information to access the Design Optimization of die.