• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.38-43
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• 2021

Permanent magnet linear synchronous motor (PMLSM) is suitable for use in cleanroom environments and have advantages such as high speed, high thrust, and high precision. If the stators are arranged in the entire moving path of the mover, there is a problem in that the installation cost increases. To solve this problem, discontinuous armature arrangement PMLSM has been proposed. In this case, the mover receives a greater detent force in the section where the stator is not arranged. When a large detent force occurs, it appears as a ripple component of the thrust during PMLSM operation. If the shape of the stator is changed to reduce the detent force, the characteristics of the back EMF are changed. Therefore, in this paper, the detent force and the harmonic components of back EMF were reduced through multi-purpose shape optimization. To this end, the FEA model was constructed and main effect analysis was performed on the major shape variables affecting each objective function. Then, the optimal shape that minimizes the objective function was derived through the response surface analysis method.

• Advances in materials Research
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• v.13 no.1
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• pp.1-18
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• 2024

The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm²) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm²) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.192-197
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• 2015

In many fields, the importance of reducing weight is increasing. A product should be designed such that it is profitable, by lowering costs and exhibiting better performance than other similar products. In this study, the mass and deflection of steel structures have to be reduced as objective functions under constraint conditions. To reduce computational analysis time, central composite design(CCD) and D-Optimal are used in design of experiments(DOE). The accuracy of approximate models is evaluated using the $R^2$ value. In this study, the objective functions are multiple, so the non-dominant sorting genetic algorithm(NSGA-II), which is highly efficient, is used for such a problem. In order to verify the validity of Pareto solutions, CAE results and Pareto solutions are compared.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.3
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• pp.308-313
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• 2015

In this research, a multi-objective optimal design of a scroll compressor lower frame was approximated, and the design parameters of the lower frame were selected. The sensitivity of the design parameters was induced through a parameter analysis, and the thickness was determined to be the most sensitive parameter to stress and deflection. All of the design parameters regarding the mass are sensitive factors. It was formulated for the problem about stress and deflection to be caused by the axial load. The sensitivity of the design variables was determined using an orthogonal array for the parameter analysis. Using the central composite and D-optimal designs, a second polynomial approximation of the objective and constraint functions was formulated and the accuracy was verified through an R-square. These functions were applied to the optimal design program (NSGA-II). Through a CAE analysis, the effectiveness of the central composite and D-optimal designs was determined.

• Journal of Ocean Engineering and Technology
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• v.27 no.1
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• pp.85-92
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• 2013

This paper deals with the resonant type of a WEC (wave energy converter) and the determination method of its geometric parameters which were obtained to construct the robust and optimal structure, respectively. In detail, the optimization problem is formulated with the constraints composed of the response surfaces which stand for the resonance period(heave, pitch) and the meta center height of the buoy. Use of a signal-to-noise ratio calculated from normalized multi-objective results with the weight factor can help to select the robust design level. In order to get the sample data set, the motion responses of the power buoy were analyzed using the BEM (boundary element method)-based commercial code. Also, the optimization result is compared with a robust design for a feasibility study. Finally, the power efficiency of the WEC with the optimum design variables is estimated as the captured wave ratio resulting from absorbed power which mainly related to PTO (power take off) damping. It could be said that the resultant of the WEC design is the economical optimal design which satisfy the given constraints.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1323-1328
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• 2011

In the current design process for the lower arm used in automobile parts, an optimal solution of its various design variables should be found through exploration of the design space approximated using the response surface model formulated with a first- or second-order polynomial equation. In this study, a multi-level computational DOE (design of experiment) was carried out to explore the design space showing nonlinear behavior, in terms of factors such as the total weight and applied stress of the lower arm, where a fractional-factorial orthogonal array based on the artificial neural network model was introduced. In addition, the tolerance robustness of the optimal solution was estimated using a tolerance optimization with six sigma constraints, taking into account the tolerances occurring in the design variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.7
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• pp.673-679
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• 2015

In this study, the nondominated sorting genetic algorithm (NSGA-II) is used to obtain the optimized proportional-integral-derivative (PID) gain value that can quickly recover the motion of a quadcopter after a disturbance. Prior to PID control, the four-rotor quadcopter interval was defined using computational fluid dynamics (CFD). Through the definition of this model, the PID control algorithm was generated. To construct a response surface model, D-optimal programming was used for the generation of experimental points. For this purpose, a gain value that satisfies both the roll and altitude PID gain values is obtained. Using the NSGA-II, the gain value of shorten time of the quadcopter motion control can be optimized.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4697-4706
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• 2010

This paper suggested the optimal operating design method using simulation and ANP(Analytic Network Process) for mass-customization in the automotive component manufacturing industry. For this, first of all, we built the simulation model including various and complex factors in the field, and estimated the meta-model by RSM(Response Surface Method). Secondly using ANP, we calculated the weight of relative importance of evaluation factors gathered from decision makers. And then, we proposed the optimal operation designs by MOGA(Multi-Objective Genetic Algorithm), analyzed results of them. Moreover, by comparing the results with the consequences using AHP(Analytic Hierarchy Process), we showed its superiority of suggested method to the manner using AHP, because it reflects inner, outer dependency, and inter-relation among judgement factors. In conclusion, through this process, we can present the better way to serve mover effective, precise, and accurate information to decision makers when they build operation design for mass-customization system as automotive parts production system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.377-386
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• 2021

The A60 class deck penetration piece is a fire-resistant system installed on a horizontal compartment to prevent flame spreading and protect lives in fire accidents in ships and offshore plants. This study deals with approximate optimization using discrete variables for the fire resistance design of an A60 class deck penetration piece using different surrogate models and a genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class deck penetration piece. For the approximate optimization of the piece, the length, diameter, material type, and insulation density were applied to discrete design variables, and temperature, productivity, and cost constraints were considered. The approximate optimum design problem based on the surrogate models was formulated such that the discrete design variables were determined by minimizing the weight of the piece subjected to the constraints. The surrogate models used in the approximate optimization were the response surface model, Kriging model, and radial basis function-based neural network. The approximate optimization results were compared with the actual analysis results in terms of approximate accuracy. The radial basis function-based neural network showed the most accurate optimum design results for the fire resistance design of the A60 class deck penetration piece.

• Journal of Aerospace System Engineering
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• v.13 no.3
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• pp.78-86
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• 2019

This paper describes the stiffness optimization of the torsion spring hinge of the large SAR antenna considering the deployment performance. A large SAR antenna is folded in a launch environment and then unfolded when performing a mission in orbit. Under these conditions, it is very important to find the proper stiffness of the torsion spring hinge so that the antenna panels can be deployed with minimal impact in a given time. If the torsion spring stiffness is high, a large impact load at the time of full deployment damages the structure. If it is weak, it cannot guarantee full deployment due to the deployment resistance. A multi-body dynamics analysis model was developed to solve this problem using RecurDyn and the development performance were predicted in terms of: development time, latching force, and torque margin through deployment analysis. In order to find the optimum torsion spring stiffness, the deployment performance was approximated by the response surface method (RSM) and the optimal design was performed to derive the appropriate stiffness value of the rotating springs.