• 한국기계가공학회지
• /
• 제7권1호
• /
• pp.22-31
• /
• 2008

The operating window method is a novel approach in quality improvement. But it has not received deserved attention in academic research. If a critical factor for competing failure modes can be identified, the probability of failure can be reduced by widening the operating window of this factor. Traditional SN ratio for the operating window advocated by Taguchi has a critical shortcoming, which has been derived under the assumption that failure rates are determined by the operating window factor only. A new metric for robustness is given for the operating window method, which has relaxed the restrictive assumption of Taguchi's SN ratio. And procedures for determining optimal conditions based on the new metric is presented. The effectiveness of the proposed approach over the traditional practice is tested with the aid of a wave soldering process.

• 한국추진공학회:학술대회논문집
• /
• 한국추진공학회 2003년도 제21회 추계학술대회 논문집
• /
• pp.145-150
• /
• 2003

The present study aims to optimize the performance of the Two-Stage Gas Gun by using the experimentally obtained data. RSM(Response Surface Method) was adopted in the optimization process to find the operating parameter than can maximize the projectile speed with the minimum number of tests. To decide the test points which results can consist of the response surface, 3$^{k}$ full factorial method was used, and the design variables were chosen with piston mass and 2$^{nd}$ driver fill pressure. The response surface was composed by nine test results and consequently the optimization was done with GENOCOP III, inherently GA code, in order to seek the optimal test point. The optimal test condition from the response surface was verified by the experiment. Results showed that the optimization process with response surface can successfully predict the test results fairly well. This study shows the possibility of performance optimization for the experimental facilities using numerical optimization algorithm.

• 유체기계공업학회:학술대회논문집
• /
• 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
• /
• pp.543-544
• /
• 2006

Shape optimization of a transonic axial compressor rotor operating at the design flow condition has been performed using three-dimensional Navier-Stokes analysis and three different surrogate models: i.e.., Response Surface Method(RSM), Kriging Method, and Radial Basis Function(RBF). Three design variables of blade sweep, lean and skew are introduced to optimize the three-dimensional stacking line of the rotor blade. The object function of the shape optimization is selected as an adiabatic efficiency. Throughout the shape optimization of the rotor blade, the adiabatic efficiency is increased for the three different surrogate models. Detailed flow characteristics at the optimal blade shape obtained by different optimization method are drawn and discussed.

• Journal of Mechanical Science and Technology
• /
• 제18권10호
• /
• pp.1829-1836
• /
• 2004

This study presents the performance optimization of hypervelocity launcher system by using the experimentall data. During the optimization, the RSM (Response Surface Method) is adopted to find the operating parameters that could maximize the projectile speed. To construct a reliable response surface model, 3 full factorial method is used with the selected design variables, such as piston mass and 2 driver fill pressure. Nine test data could successfully construct the reasonable response surface, which used to yield the optimal operational conditions of the system using the genetic algorithm. The optimization results are confirmed by the experimental test with a good accuracy. Thus, the optimization can improve the performance of the facility.

• 대한전기학회논문지
• /
• 제32권4호
• /
• pp.145-154
• /
• 1983

This paper presents a new method for optimal real and reactive power dispatch for the economic operation of a power system. Unlike the usual approach of minimizing the transmission loss, this method minimizes the total production cost not only for the real power optimization problem, but also for the reactive power optimization. The control variables are real power generation of units for real power optimization, and reactive power optimization. The constraints are the operating limits on these control variables and the limits on the bus voltages. Methematical models are developed to represent the sensitivity relationships between dependent and control variables for both real and reactive power optimization modules, and thus eliminate the use of B-coefficients. In order to handle many functional inequality constraints, a modified version of the gradient projection method is developed for optimization procedure, and has shown a remarkable advantage in computation efficiency.

• 대한조선학회논문집
• /
• 제57권1호
• /
• pp.45-51
• /
• 2020

In this study, we developed an allocation optimization system for supply chain management in the shipbuilding and offshore construction industry. Supply chain operation is a way of operating manufacturing company responsible for the procurement of outfitting parts. The method about how to allocate the manufacturing volume to each partner company includes important decisions. According to the allocation method, the stability of the material supplied to the final installation process is guaranteed. We improved the allocation method that was previously decided by the person in charge. Based on the optimization engine, a system is developed that can automatically allocate the production volume. For optimization model configuration, factors affecting the volume allocation were analyzed and modeled as constraint factors. A target function is defined to minimize the difference in the load variance of each partner company. In order to use the same type of volume allocation engine for various outfitting products, the amount of work done by the partner company was standardized. We developed an engine that can allocate the same production load of each production partner. Using this engine, the operating system was developed and applied to the actual offshore project. It has been confirmed that the work load variance of suppliers can be maintained uniformly using the optimization engine rather than manual method. By this system, we stabilize the manufacturing process of partner suppliers.

• 한국전산유체공학회지
• /
• 제21권3호
• /
• pp.39-47
• /
• 2016

We conducted a multi-stage optimization to secure the desired performance of a centrifugal fan for home appliance in an early stage of product development. In optimization, the static pressure at the outlet of the fan is chosen as an objective function that is to be maximized, providing the required flow rate at the operating point of the fan. The optimization procedure begins with parameters for an initial baseline fan design. The baseline design is optimized by using a commercial optimization package. Accordingly, the corresponding blade models with a set of geometrical parameters are generated. Flow through a fan is simulated by solving the Reynolds-averaged Navier-Stokes equations. A multi-stage optimization scheme is employed to determine the family of optimum values for the parameters, leading to the pressure increase at the outlet of the fan. To validate the numerically obtained optimal design parameters, we fabricated the three types of fans using rapid prototyping and assessed the performance using a fan tester. Experimental results show that the design parameters at each stage satisfy the goal of optimization. The multi-stage optimization process turned out to be a useful tool in the development of a centrifugal fan.

• 해양환경안전학회지
• /
• 제24권3호
• /
• pp.367-372
• /
• 2018

The objective of this paper is to optimize the cross-section of aluminum decking units used in the bass boats under operating conditions, and to verify the optimized model from the results via by ANSYS software. Aluminum decking unit is needed to endure specific loading while leisure activity and sailing. For a stiffer and more cost-neutral aluminum decking unit, optimization is often considered in the naval and marine industries. This optimization of the aluminum decking unit is performed using the ANSYS program, which is based on the topology optimization method. The generation of finite element models and stress evaluations are conducted using the ANSYS Multiphysics module, which is based on the Finite Element Method (FEM). Through such a series of studies, it was possible to determine the most suitable case for satisfying the structural strength found among the phase-optimized aluminum deck units in bass boats. From these optimization results, CASE 1 shows the best solution in comparison with the other cases for this optimization. By linking the topology optimization with the structural strength analysis, the optimal solution can be found in a relatively short amount of time, and these procedures are expected to be applicable to many fields of engineering.

• Journal of Electrical Engineering and Technology
• /
• 제10권1호
• /
• pp.56-63
• /
• 2015

The optimization is an important role in wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. In this paper, the real coded biogeography based optimization is proposed to minimize the operating cost with optimal setting of equality and inequality constraints of thermal power system. The proposed technique aims to improve the real coded searing ability, unravel the prematurity of solution and enhance the population assortment of the biogeography based optimization algorithm by using adaptive Gaussian mutation. This algorithm is demonstrated on the standard IEEE-30 bus system and the comparative results are made with existing population based methods.

• 한국항공운항학회지
• /
• 제26권2호
• /
• pp.54-60
• /
• 2018

This paper contains the multi-mission scheduling optimization of UAV within a given operating time. Mission scheduling optimization problem is one of combinatorial optimization, and it has been shown to be NP-hard(non-deterministic polynomial-time hardness). In this problem, as the size of the problem increases, the computation time increases dramatically. So, we applied the genetic algorithm to this problem. For the application, we set the mission scenario, objective function, and constraints, and then, performed simulation with MATLAB. After 1000 case simulation, we evaluate the optimality and computing time in comparison with global optimum from MILP(Mixed Integer Linear Programming).