• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.61-66
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• 2018

The objective of this research study is to investigate the optimal process parameters of electrical discharge machining (EDM) on SCM440 steel with copper as a tool electrode. The effect of various process parameters on machining performance is investigated in this study. Modern ED machinery is capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, etc. This paper reports the results of an experimental investigation by Taguchi method carried out to study the effects of machining parameters on material surface roughness in electric discharge machining of SCM440 steel. To predict the optimal condition, the experiments are conducted by using Taguchi's L27 orthogonal array. The work material was ED machined with copper electrodes by varying the pulsed current, pulse on-time, voltage, servo speed and spark speed. Investigations indicate that the surface roughness is strongly depend on pulsed current.

• Coupled systems mechanics
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• v.11 no.2
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• pp.133-149
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• 2022

The accurate prediction of elastoplasticity under prescribed workloads is essential in the optimization of engineering structures. Mechanical experiments are carried out with the goal of obtaining reliable sets of material parameters for a chosen constitutive law via inverse identification. In this work, two sample geometries made of high strength steel plates were evaluated to determine the optimal configuration for the identification of Ludwik's nonlinear isotropic hardening law. Finite element model updating(FEMU) was used to calibrate the material parameters. FEMU computes the parameter changes based on the Hessian matrix, and the sensitivity fields that report changes of computed fields with respect to material parameter changes. A sensitivity analysis was performed to determine the influence of the sample geometry on parameter identifiability. It was concluded that the sample with thinned gauge region with a large curvature radius provided more reliable material parameters.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.70-79
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• 1996

In off-line process optimization, process parameters are controlled such that the process is robust against changes in equipment conditions and incoming materials. The off-line methods, however, are not effective when the changes are so large that process parameters need to be adjusted. On-line control can respond to such large changes, but process uniformity has not been controlled on-line due to the difficulties in modeling. This paper is aimed at developing a new on-line control methodology where the uniformity is controlled effectively. The process variability is categorized based on the physical considerations, and the process parameters are classi- fied considering their effects on the categorized process variabilities. On-line control is performed with the properly selected process parameters so that robustness may not be degraded. The developed methodology is applied to the single wafer plasma etching processes, which resulted in both higher within-a-wafer uniformity and compens- ation of the incoming material non-uniformity.

• Steel and Composite Structures
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• v.21 no.1
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• pp.217-247
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• 2016

Five extended cylindrical reticulated shells are proposed by changing distribution rule of diagonal rods based on three fundamental types. Modeling programs for fundamental types and extended types of cylindrical reticulated shell are compiled by using the ANSYS Parametric Design Language (APDL). On this basis, conditional formulas are derived when the grid shape of cylindrical reticulated shells is equilateral triangle. Internal force analysis of cylindrical reticulated shells is carried out. The variation and distribution regularities of maximum displacement and stress are studied. A shape optimization program is proposed by adopting the sequence two-stage algorithm (RDQA) in FORTRAN environment based on the characteristics of cylindrical reticulated shells and the ideas of discrete variable optimization design. Shape optimization is achieved by considering the objective function of the minimum total steel consumption, global and locality constraints. The shape optimization for three fundamental types and five extended types is calculated with the span of 30 m~80 m and rise-span ratio of 1/7~1/3. The variations of the total steel consumption along with the span and rise-span ratio are analyzed with contrast to the results of shape optimization. The optimal combination of main design parameters for five extended cylindrical reticulated shells is investigated. The total steel consumption affected by distribution rule of diagonal rods is discussed. The results show that: (1) Parametric modeling method is simple, efficient and practical, which can quickly generate different types of cylindrical reticulated shells. (2) The mechanical properties of five extended cylindrical reticulated shells are better than their fundamental types. (3) The total steel consumption of cylindrical reticulated shells is optimized to be the least when rise-span ratio is 1/6. (4) The extended type of three-way grid cylindrical reticulated shell should be preferentially adopted in practical engineering. (5) The grid shape of reticulated shells should be designed to equilateral triangle as much as possible because of its reasonable stress and the lowest total steel consumption.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.451-458
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• 2014

This study is a practical research for setting a process of making references of design decision and guidlines of limitation in the movement from the design development to the construction design by StrAuto. StrAuto, as a parametric modeling and optimization tool for building structure, enables a quantity of design cases to be analyzed automatically by changing parameters of sturctural properties. So the designer using StrAuto can check a lot of analysis data crossing thousands of cases, see which case is out of acceptable range, and make a decision for design and optimization. In this thesis, the application of StrAuto optimization process to the residence tower UIC project shows the practical applicability in the construction design and value engineering. StrAuto optimized ideally volume of core walls by 31.3% and lead the final revised model applied to the construction design to reduce volume by 18.1%. The significance of this research is the implementation of process that the designer can quickly review a number of cases and get a direction for construction design and optimization after design development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.575-594
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• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.233-242
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• 2021

In this paper, as a liberal arts course for non-majors, we proposed a supervised learning artificial neural network parameter optimization method and a basic education method for activation function to design a basic artificial neural network subject curriculum. For this, a method of finding a parameter optimization solution in a spreadsheet without programming was applied. Through this training method, you can focus on the basic principles of artificial neural network operation and implementation. And, it is possible to increase the interest and educational effect of non-majors through the visualized data of the spreadsheet. The proposed contents consisted of artificial neurons with sigmoid and ReLU activation functions, supervised learning data generation, supervised learning artificial neural network configuration and parameter optimization, supervised learning artificial neural network implementation and performance analysis using spreadsheets, and education satisfaction analysis. In this paper, considering the optimization of negative parameters for the sigmoid neural network and the ReLU neuron artificial neural network, we propose a training method for the four performance analysis results on the parameter optimization of the artificial neural network, and conduct a training satisfaction analysis.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.1
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• pp.1-12
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• 2016

In this study, CFD model for a Heat Exchange Steam Reformer (HESR) used for a 10kW SOFC system is developed for the design optimization of the HESR. The model is used to explore the effect of design parameters on the performance of the HESR. In the HESR, heat is delivered from the hot gas channel to the fuel channel to supply the heat required for the fuel reforming. In the fuel channel where the fuel is reformed, thermo-fluid dynamics, heat transfer, and chemical reaction are considered to predict the performance of the reformer. The model is validated with experimental data within 2~3% error. The validated model is used for the parametric study of the HESR design. Channel length, channel diameter, and flow direction are selected as the design parameters. The effects of the HESR design parameters on the outlet temperature, outlet H2 mole fraction, and pressure drop across the reformer are presented using the model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.560-567
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• 2020

Incremental Sheet Forming (ISF) is a unique sheet-forming technique. The process is a die-less sheet metal manufacturing process for rapid prototyping and small batch production. In the forming process, the critical parameters affecting the formability of sheet materials are the tool diameter, step depth, feed rate, spindle speed, etc. This study examined the effects of these parameters on the formability in the forming of the varying wall angle conical frustum model for a pure Al3004 sheet with 1mm in thickness. Using Minitab software based on Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA), a second order mathematical prediction model was established to predict and optimize the wall angle. The results showed that the maximum forming angle was 87.071° and the best combination of these parameters to give the best performance of the experiment is as follows: tool diameter of 6mm, spindle speed of 180rpm, step depth of 0.4mm, and feed rate of 772mm/min.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.660-665
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• 2014

Optimization of process parameters in polymer extrusion is an important task to reduce manufacturing cost. To determine the optimum values of the process parameters, it is essential to find their influence on the elongation of polymer breathable thin film. The significance of six important process parameters namely, extruder cylinder temperature, extruder speed, extruder dies temperature, cooling roll temperature, stretching ratio, stretching roll temperature on breathable film elongation of polymer extrusion was determined. Moreover, this paper presents the application of Taguchi method and analysis of variance(ANOVA) for maximization of the breathable film elongation influenced by extrusion parameters. The optimum parameter combination of extrusion process was obtained by using the analysis of signal-to-noise ratio. The conclusion revealed that stretching ratio were the most influential factor on the film elongation. The best results of film elongation were obtained at lower stretching ratio.