• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.5
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• pp.575-582
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• 2011

A cleaning blade is an attachment installed in the toner cartridge of a laser printer for removing the residual toner from an organic photo-conductive drum. There have been many studies on the performance and life of the rubber blade. We focus on optimally designing the blade shape parameters to minimize the maximum stress of the blade while satisfying design constraints on the cleaning performance and part interference. The blade is optimally designed using a design of experiments, meta-models and an optimization algorithm implemented in PIAnO (process integration, automation, and optimization), a commercial PIDO (process integration and design optimization) tool. We integrate the CAE tools necessary for the structural analysis of the cleaning blade, automate the analysis procedure, and optimize the solution using PIAnO. We decreased the maximum stress by 32.6% in comparison with that of the initial design.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• The Journal of the Acoustical Society of Korea
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• v.32 no.4
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• pp.317-328
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• 2013

In this paper, the optimization has been performed to design a multi-layer structure that is used as a structure for noise reduction of acoustic sonar sensors in underwater vehicles. Two design goals are considered to reduce self-noise from own machineries and to enhance acoustic signals detected from outside. Both distinct and continuous design parameters have been used such as selection of material properties of each layer and thickness of each layer, respectively. The sensitivity of design parameters has been analyzed and the evolutionary algorithm has been implemented for design optimization. For design optimization process, each of the design goals and the two combined design goals have been considered to analyze the achievement of those design goals.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.9
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• pp.109-115
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• 2008

The cleaning process of contaminant particles adhering to the microchips, integrated circuits (ICs) or the like is essential in modern microelectronics industry. In the cleaning process particularly working with the application of inert gases, the removal of contaminant particles of submicron scale is very difficult because the particles are prone to reside inside the boundary layer of the working fluid, The use of cryogenic $CO_2$ cleaning method is increasing rapidly as an alternative to solve this problem. In contrast to the merits of high efficiency of this process in the removal of minute particles compared to the others, even fundamental parametric studies for the optimal process design in this cleaning process are hardly done up to date, In this study, we attempted to measure the cleaning efficiency with the variations of some principal parameters such as mass flow rate, injection distance and angle, and tried to draw out optimal cleaning conditions by measuring and evaluating an effective cleaning width called $d_{50}$.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05c
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• pp.228-232
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• 2002

The rise throughput and the stability in the device fabrication can be obtained by applying chemical mechanical polishing(CMP) process in 0.18 ${\mu}m$ semiconductor device. However it does have various problems due to the CMP equipment. Especially, among the CMP components, process variables are very important parameters in determining removal rate and non-uniformity. In this paper, We studied the DOE(design of experiment) method for the optimized CMP process. Various process variations, such as table and head speed, slurry flow rate and down force, have investigated in the viewpoint of removal rate and non-uniformity. Through the above DOE results, we could set-up the optimal process parameters.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.3
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• pp.251-257
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• 2012

The flight controller should meet the flying qualities, stability margins, and time response requirement according to the class of a target aircraft or UAV. Classical design process of PID controller is a very time consuming process and needed trial and erros. The best way is to apply the multi-disciplinary optimization algorithm to meet the numerous constraints of controller requirements. This paper presents how multi-objective parameter optimization (CONDUIT) can be used to determine many design parameters of lateral stability and augmentation system for roll and heading controller of the small UAV. To verify the effectiveness of applying the optimization method, designed controller using optimization are compared with the baseline controller that is designed only considering the time responses.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.4
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• pp.28-33
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• 2015

In this study, the optimal design for the support and the binding device for the protection of crops for the maximum allowable stress of the shape necessary to minimize volume has been proposed. Optimization of the support and the binding device for the crops should be designed to support businesses in terms of profit, in part to reduce the material, and to profit from the ease and speed of working that part of the farmers. We used CATIA for the mechanical design and the ANSYS program for the structural analysis. Additionally, the optimization was performed by PIAnO with seven design variables for the binding device and three parameters for the support. The weight method using a multi-objective function was also determined by the Pareto optimal solution. The volume of the binding device in the optimum design result was found to be reduced by 16%, from $2.278e-005m^3to1.912e-005m^3$. From the result, we confirmed the effectiveness of the design method proposed as a multi-objective function optimization problem.

• Journal of the Korea Society for Simulation
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• v.12 no.3
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• pp.31-40
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• 2003

This paper studies an optimal policy for a certain class of (s, S) inventory control systems, where the demands are characterized by the renewal arrival process. To minimize the average cost over a simulation period, we apply a stochastic optimization algorithm which uses the gradients of parameters, s and S. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. The optimal estimates of s and S from our simulation results are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and inter-arrival times of demands. Another direction involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

• Journal of Ship and Ocean Technology
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• v.5 no.2
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• pp.14-26
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• 2001

This paper presents a novel design approach that could generate structural design alternatives having different topologies and then, select the optimum structure from them with simulataneously determining its optimum design variables related to geometry and the member size subjected to the multiple objective design environments. For this purpose, a specialized genetic algorithm, called StrGA_DeAl + MOGA, which can handle the design alternatives and multi-criteria problems very effectively, is developed for the optimal structural design. To validate the developed method, method, plain truss design problems are considered as illustrative example. To begin with, some possible topological of the truss structure are suggested based on the stability criterion that should be satisfied under the given loading condition. Then, with the consideration of the given multi-criteria, several different topology forms are selected as design alternatives for the second step of the conceptual design process. Based on the chosen topolgy of truss structures, the sizing or shaping optimization process starts to determine the optimum design parameters. Ten-bar truss problems are given in the paper to confirm the above concept and methodology.

• Structural Engineering and Mechanics
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• v.82 no.5
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• pp.667-678
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• 2022

Moment-resisting frames (MRFs) are among the most conventional steel structures for mid-rise buildings in many earthquake-prone cities. Here, a simplified performance-based methodology is proposed for the seismic collapse capacity assessment of these buildings. This method employs a novel multi-mode pushover analysis to determine the engineering demand parameters (EDPs) of the regular steel MRFs up to the collapse prevention (CP) performance level. The modal combination coefficients used in the proposed pushover analysis, are obtained from two metaheuristic optimization algorithms and a fitting procedure. The design variables for the optimization process are the inter-story drift ratio profiles resulting from the multi-mode pushover analyses, and the objective values are the outcomes of the incremental dynamic analysis (IDA). Here, the collapse capacity of the structures is assessed in three to five steps, using a modified IDA procedure. A series of regular mid-rise steel MRFs are selected and analyzed to calculate the modal combination coefficients and to validate the proposed approach. The new methodology is verified against the current existing approaches. This comparison shows that the suggested method more accurately evaluates the EDPs and the collapse capacity of the regular MRFs in a robust and easy to implement way.