• Transactions of Materials Processing
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• v.18 no.5
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• pp.392-400
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• 2009

Clinching is a method of joining sheet metals together. This process can be substituted for the resistance spot welding on the joining of aluminum alloys. However, the joining strength of the clinching is lower than that of welding and riveting. The objective of this paper is to evaluate the effect of shape parameters of tools on the joining strength of the clinching and to optimize clinching tools. Twelve parameters have been selected as shape parameters on the clinching tools such as punch and die. The design of experiments (DOE) method is employed to investigate the effect of the shape parameters of tools on the joining strength of the clinching. The neck thickness and undercut of the clinched sheet metal after the clinching, and the separation load at detaching are estimated from the result of FEA using DEFORM. Optimal combination of shape parameters to maximize the joining strength of clinching is determined on the basis of the result of DOE and FEA. In order to validate the result of DOE and FEA, the experiment of clinching is performed for the optimal combination of shape parameters. It is shown from the result of the experiment that optimization of shape parameters improves the joining strength of clinching.

• Korean Journal of Environmental Biology
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• v.22 no.1
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• pp.167-170
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• 2004

A self-directing optimization procedure was applied to determine the best environmental factors in operating the bioreactor. The self-directing optimization process was employed to determine the best conditional combination of multi parameters, pH, temperature, aeration rate and mixing rate toy maximal production of chitinase by Trichoderma harzianum SJG-99721 in batch mode fermentation. Among these factors, the parameters of pH and aeration rate were found to be particularly important on mycellial growth and chitinase activity. pH 4.89, an aeration rate of 3.22 ι per minute and an agitation rate of 225 rpm was found to be the best combination. By the optimization, chitinase activity was dramatically increased from an initial value of 4.221 U under basic conditions to n final value of 16.825 U.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.3
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• pp.227-234
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• 2020

This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.225-229
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• 2000

Burrs formed during face milling operations are very hard to characterize like other machining burrs because there are many parameters which affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complicated combination effects between the parameters. In this paper, Taguchi method, which is a systematic optimization application of design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization. Optimized experimental conditions are provided to show the effectiveness of this approach.

• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.501-513
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• 2020

In the present work, the optimization of machining parameters to achieve the desired technological parameters such as surface roughness, tool radial vibration and material removal rate have been carried out using response surface methodology (RSM). The hard turning of EN19 alloy steel with coated carbide (GC3015) cutting tools was studied. The main problem faced in manufacturer of hard and high precision components is the selection of optimum combination of cutting parameters for achieving required quality of surface finish with maximum production rate. This problem can be solved by development of mathematical model and execution of experiments by RSM. A face centred central composite design (FCCD), which comes under the RSM approach, with cutting parameters (cutting speed, feed rate and depth of cut) was used for statistical analysis. A second-order regression model were developed to correlate the cutting parameters with surface roughness, tool vibration and material removal rate. Consequently, numerical and graphical optimization were performed to obtain the most appropriate cutting parameters to produce the lowest surface roughness with minimal tool vibration and maximum material removal rate using desirability function approach. Finally, confirmation experiments were performed to verify the pertinence of the developed mathematical models.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.775-781
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• 2006

An intelligent optimization method for designing Fractional Order PID(FOPID) controllers based on Particle Swarm Optimization(PSO) is presented in this paper. Fractional calculus can provide novel and higher performance extension for FOPID controllers. However, the difficulties of designing FOPID controllers increase, because FOPID controllers append derivative order and integral order in comparison with traditional PID controllers. To design the parameters of FOPID controllers, the enhanced PSO algorithms is adopted, which guarantee the particle position inside the defined search spaces with momentum factor. The optimization performance target is the weighted combination of ITAE and control input. The numerical realization of FOPID controllers uses the methods of Tustin operator and continued fraction expansion. Experimental results show the proposed design method can design effectively the parameters of FOPID controllers.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.1
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• pp.63-73
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• 2014

For robust stability analysis of parameters uncertainty missiles, the traditional frequency domain method can only analyze each respective channel at several interval points within uncertain parameter space. Discontinuous calculation and couplings between channels will lead to inaccurate analysis results. A method based on the ${\nu}$-gap metric is proposed, which is able to comprehensively evaluate the robust stability of missiles with uncertain parameters; and then a genetic-simulated annealing hybrid optimization algorithm, which has global and local searching ability, is used to search for a parameters combination that leads to the worst stability within the space of uncertain parameters. Finally, the proposed method is used to analyze the robust stability of a re-entry missile with uncertain parameters; the results verify the feasibility and accuracy of the method.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.256-265
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• 2014

Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

• Structural Engineering and Mechanics
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• v.56 no.6
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• pp.959-982
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• 2015

In this study, a non-stationary random earthquake Clough-Penzien model is used to describe earthquake ground motion. Using stochastic direct integration in combination with an equivalent linear method, a solution is established to describe the non-stationary response of lead-rubber bearing (LRB) system to a stochastic earthquake. Two parameters are used to develop an optimization method for bearing design: the post-yielding stiffness and the normalized yield strength of the isolation bearing. Using the minimization of the maximum energy response level of the upper structure subjected to an earthquake as an objective function, and with the constraints that the bearing failure probability is no more than 5% and the second shape factor of the bearing is less than 5, a calculation method for the two optimal design parameters is presented. In this optimization process, the radial basis function (RBF) response surface was applied, instead of the implicit objective function and constraints, and a sequential quadratic programming (SQP) algorithm was used to solve the optimization problems. By considering the uncertainties of the structural parameters and seismic ground motion input parameters for the optimization of the bearing design, convex set models (such as the interval model and ellipsoidal model) are used to describe the uncertainty parameters. Subsequently, the optimal bearing design parameters were expanded at their median values into first-order Taylor series expansions, and then, the Lagrange multipliers method was used to determine the upper and lower boundaries of the parameters. Moreover, using a calculation example, the impacts of site soil parameters, such as input peak ground acceleration, bearing diameter and rubber shore hardness on the optimization parameters, are investigated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.567-570
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• 2000

Optimization of structure of a high-precision stamping press structure is performed by combination of Taguchi Method and finite element analysis. Too much difference in the stiffness between hydrostatic bearing linear guide and press structure is observed. Efforts are made to level up the stiffness of press structure to the level of hydrostatic bearing's. Some important design parameters are identified and discussed.