• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.28 no.4
• /
• pp.85-93
• /
• 2005

This paper is designed a VSI ${\overline{X}}$-CRL synthetic control chart in aspect of economy. We found the optimal sampling interval and various control limit factors under various cost parameters using cost function, proposed Lorenzen and Vance. Optimal design parameters include the sample size, control limit width, sampling interval, CRL/S chart control limit; L. Comparison and analysis of cost parameters are applied between synthetic VSI ${\overline{X}}$-CRL chart and FSI ${\overline{X}}$-CRL chart. The result of this paper shows that VSI ${\overline{X}}$-CRL chart brings cost-cutting effect of 3.04% control expense less than FSI control chart. It may not be difficult to establish the optimal economic control parameters to apply the practical cost parameters in the field.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1508-1511
• /
• 1997

In this paper, design parameters of Rapid Thermal Processing(RrW) to minimize the wafer tempera ture uniformity errors are proposed. 1,anip ling positions and the wafer height are important parameters for waf er temperature uniformity in R'I'P. We propose the method to seek lamp ling positions and the wafer height for optimal temperature uniformity. l'he ~~roposed method is applied to seek optimal lamp ling positions and the waf er height of 8 inch wafer. 'I'o seek the optimal lamp ling positions and the wafer height, we var\ulcorner. lamp ling 110s itions and the wafer height and then formulate the wafer temperature uniformity problem to the linear programmi ng problem. Finally, it is shown that the wafer temperature uniformity in RI'I' designed by optimal prarneters is improved to comparing with Ii'l'P designed by the other method.

• 한국신재생에너지학회:학술대회논문집
• /
• 2008.05a
• /
• pp.368-371
• /
• 2008

The optimal operation condition of gasifier is one of the most important parameters to increase efficiency and reliability in IGCC plant. Also the prediction of the syngas composition and quantity must be predicted to carry out process design of the gasification plant. However, the gasifier process licensor are protective with information on process design and optimal gasifier design conditions. So, the most of process studies in the engineering company for gasification plant have carried out to look for key parameters and optimal design conditions using several prediction methods. In this paper, we present the estimated preliminary optimal operation condition of the 300MW Demonstration Entrain Flow Gasifier using Aspen Plus. The gasifier operation temperature considering slag flow was predicted by FactSage software and Annen Model.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.4
• /
• pp.422-434
• /
• 1997

In this paper, a two-stage kinematic optimal design for a 3 degree of-freedom (DOF) excavator subsystem, which consists of boom, arm and bucket, is performed. The objective of the first stage is to find the optimal parameters of the joint-actuating mechanisms which maximize the force-torque transmission ratio between the hydraulic actuator and the rotating joint. The objective of the second stage is to find the optimal link parameters which maximize the isotropic characteristic of the excavator subsystem throughout the workspace. It is illustrated that kinematic/dynamic performances of the kinematically optimized excavator subsystem have improved compared to those of original HE280 excavator, with respect to three performance indices such as maximum load handling capacity, maximum velocity capability, and acceleration capability.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.617-622
• /
• 1994

In this paper, we perform a two-stage, kinematic optimal design for 3 degree-of-freedom excavator system which consists of boom, arm, and bucket. The objective of the first stage is to find the optimal joint parameters which maximize the force-torque transmission ratio between the hydraulic actuator and the rotating joint. The objective of the first stage is to find the optimal link parameters which maximize the isotropic characteristic throughout the workspace. It is illustrated that performances of the optimized excavator are improved compared to those of HE280 excavator, with respect to the described performace index and maximum load handling capacity.

• International Journal of Korean Welding Society
• /
• v.3 no.2
• /
• pp.15-23
• /
• 2003

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables were wire feed rate, welding voltage, and welding speed, root opening and the output variables were bead height, bead width, penetration and back bead width. The number of level for each input variable is 8, 16, 8 and 3, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 3,072 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 48 experiments.

• Journal of Welding and Joining
• /
• v.18 no.5
• /
• pp.63-69
• /
• 2000

A genetic algorithm was applied to an arc welding process to determine near optimal settings of welding process parameters which produce good weld quality. This method searches for optimal settings of welding parameters through systematic experiments without a model between input and output variables. It has an advantage of being able to find optimal conditions with a fewer number of experiments than conventional full factorial design. A genetic algorithm was applied to optimization of weld bead geometry. In the optimization problem, the input variables was wire feed rate, welding voltage, and welding speed and the output variables were bead height, bead width, and penetration. The number of level for each input variable is 16, 16, and 8, respectively. Therefore, according to the conventional full factorial design, in order to find the optimal welding conditions, 2048 experiments must be performed. The genetic algorithm, however, found the near optimal welding conditions from less than 40 experiments.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.17 no.6
• /
• pp.587-595
• /
• 2005

The heat and flow characteristics in a parallel-flow heat exchanger were examined numerically to obtain its optimal design variables. A desirability function approach was introduced to optimize its performance with respect to the design parameters over the design domain. By varying the importance of heat transfer and pressure drop which are out put variables, the optimal values of the design parameters are examined. As a result, the us-age of the desirability function is very effective for the optimization of the design variables in a heat exchanger since the changes of optimal values are physically appropriate by varying the importance of each output variable.

• The Journal of Korean Academy of Prosthodontics
• /
• v.44 no.2
• /
• pp.185-196
• /
• 2006

Statement of problem: The researches on the influence of design variables on the stress distribution in cortical and trabecular bones and on optimal design for implant system were limited. Purpose: The purpose of this study is to identify the sensitivities of design parameters and to suggest the optimal parameters for designing the onebody type implant system. Material and methods: Stresses arising in the implant system were obtained by finite element analysis using a three dimensional model. An onebody type implant system[Oneplant (Warrantec. Co. Ltd., Korea)] was considered in this study. Vortical load(150 N) was applied on the top of the abutment along the axial direction. The initial design variables set for sensitivity analysis were radius of fixture, numbers of micro thread, numbers of power thread, height of micro thread, future length, tapered angle of future, inclined angle of thread, width of micro thread and width of power thread. The statistical technique of Design of Experiments(DOE) was applied tn the simulation model to deduce effective design parameters on stress distributions in bones. The deduced design parameters were incorporated into a fully automated design tool which is coupled with the finite element analysis and numerical optimization to determine the optimal design parameters. Results: 1. The result of sensitivity analysis showed six design variables - radius of future, tapered angle of fixture, inclined angle of thread, numbers of power thread, numbers of micro thread and height of micro thread - were more influential than the others. 2. The optimal values of design variables can be deduced by coupling finite element analysis (FEA) and design optimization tool(DOT).

• Journal of Korea Water Resources Association
• /
• v.56 no.spc1
• /
• pp.1007-1014
• /
• 2023

Two-dimensional flow analysis, a fundamental component of hydrodynamics, plays a pivotal role in numerically simulating fluid behavior in rivers and waterways. This modeling approach heavily relies on parameters such as eddy viscosity and roughness coefficient to accurately represent flow characteristics. Therefore, combination of appropriate parameters is very important to accurately simulate flow characteristics. In this study, an automation algorithm was developed and applied to find the optimal combination of parameters. Previously, when applying a two-dimensional flow analysis model, former researchers usually depend on the empirical approach, which causes many difficulties in finding optimal variable values. Using the experimental data, we tracked errors according to the combination of various parameters and applied the algorithm that can determine the optimal combination of parameters with the Python language. The automation algorithm can easily determine the most accurate combination by comparing the flow velocity error values among the two-dimensional flow analysis results among the combinations of 121 (11×11) parameters. In the perspective of utilizing automation algorithm, there is an expected high utility in promptly and straightforwardly determining the optimal combination of parameters with the smallest error.