• Title/Summary/Keyword: global optimum

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Optimization of Double Polishing Pad for STI-CMP Applications (STI-CMP 적용을 위한 이중 연마 패드의 최적화)

  • Park, Seong-U;Seo, Yong-Jin;Kim, Sang-Yong
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.51 no.7
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    • pp.311-315
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    • 2002
  • Chemical mechanical polishing (CMP) process was required for the global planarization of inter-metal dielectric(IMD), inter-level dielectric (ILD) layers of multi-layer interconnections. In this paper, we studied the characteristics of polishing pad, which can apply shallow trench isolation (STI)-CMP process for global planarization of multi-level interconnection structure. Also, we investigated the effects of different sets of polishing pad, such as soft and hard pad. As an experimental result, hard pad showed center-fast type, and soft pad showed edge-fast type. Totally, the defect level has shown little difference, however, the counts of scratch was detected less than 2 on JR111 pad. Through the above results, we can select optimum polishing pad, so we can expect the improvements of throughput and device yield.

A Global Optimal Approach for Robot Kinematics Design using the Grid Method

  • Park Joon-Young;Chang Pyung-Hun;Kim Jin-Oh
    • International Journal of Control, Automation, and Systems
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    • v.4 no.5
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    • pp.575-591
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    • 2006
  • In a previous research, we presented the Grid Method and confirmed it as a systematic and efficient problem formulation method for the task-oriented design of robot kinematics. However, our previous research was limited in two ways. First, it gave only a local optimum due to its use of a local optimization technique. Second, it used constant weights for a cost function chosen by the manual weights tuning algorithm, thereby showing low efficiency in finding an optimal solution. To overcome these two limitations, therefore, this paper presents a global optimization technique and an adaptive weights tuning algorithm to solve a formulated problem using the Grid Method. The efficiencies of the proposed algorithms have been confirmed through the kinematic design examples of various robot manipulators.

Optimum distribution of steel frame assembly for seismic retrofit of framed structures

  • Michael Adane;Seungho Chun;Jinkoo Kim
    • Steel and Composite Structures
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    • v.50 no.3
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    • pp.337-345
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    • 2024
  • This research proposed a particle swarm optimization (PSO) based seismic retrofit design of moment frame structures using a steel frame assembly. Two full scale specimens of the steel frame assembly with different corner details were attached to one-story RC frames for seismic retrofit, and the lateral load resisting capacities of the retrofitted frames subjected to cyclic loads were compared with those of a bare RC frame. The open source software framework Opensees was used to develop an analytical model for validating the experimental results. The developed analytical model and the optimization scheme were applied to a case study structure for economic seismic retrofit design, and its seismic performance was assessed before and after the retrofit. The results show that the developed steel frame assembly was effective in increasing seismic load resisting capability of the structure, and the PSO algorithm could be applied as convenient optimization tool for seismic retrofit design of structures.

A Study on the Support location Optimizations of the Beams using the Genetic Algorithm and the Sensitivity Analysis. (민감도가 고려된 유전 알고리듬을 이용한 보 구조물의 지지점 최적화에 관한 연구)

  • 이재관;신효철
    • Journal of KSNVE
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    • v.10 no.5
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    • pp.783-791
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    • 2000
  • This describes a study on the support location optimizations of the beams using the genetic algorithm and the sensitivity analysis. The genetic algorithm is a probabilistic method searching the optimum at several points simultaneously and requiring only the values of the object and constraint functions. It has therefore more chances to find the global solution and can be applied to the various problems. Nevertheless, it has such a shortcoming that it takes too many calculations, because it is ineffective in local search. While the traditional method using sensitivity analysis is of great advantage in searching the near optimum. thus the combination of the two techniques will make use of the individual advantages, that is, the superiority in global searching form the genetic algorithm and that in local searching form the sensitivity analysis. In this thesis, for the practical applications, the analysis is conducted by FEB ; and as the shapes of structures are taken as the design variation, it requires re-meshing for every analysis. So if it is not properly controlled, the result of the analysis is affected and the optimized solution amy not be the real one. the method is efficiently applied to the problems which the traditional methods are not working properly.

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Optimal Ball-end and Fillet-end Mills Selection for 3-Axis Finish Machining of Point-based Surface

  • Kayal, Prasenjit
    • International Journal of CAD/CAM
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    • v.7 no.1
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    • pp.51-60
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    • 2007
  • This paper presents an algorithm of optimal cutting tool selection for machining of the point-based surface that is defined by a set of surface points rather than parametric polynomial surface equations. As the ball-end and fillet-end mills are generally used for finish machining in a 3-axis computer numerical control machine, the algorithm is applicable for both cutters. The optimum tool would be as large as possible in terms of the cutter radius and/or corner radius which maximise (s) the material removal rate (i.e., minimise (s) the machining time), while still being able to machine the entire point-based surface without gouging any surface point. The gouging are two types: local and global. In this paper, the distance between the cutter bottom and surface points is used to check the local gouging whereas the shortest distance between the surface points and cutter axis is effectively used to check the global gouging. The selection procedure begins with a cutter from the tool library, which has the largest cutter radius and/or corner radius, and then adequacy of the point-density is checked to limit the accuracy of the cutter selection for the point-based surface within tolerance prior to the gouge checking. When the entire surface is gouge-free with a chosen cutting tool then the tool becomes the optimum cutting tool for a list of cutters available in the tool library. The effectiveness of the algorithm is demonstrated considering two examples.

Initial Design Domain Reset Method for Genetic Algorithm with Parallel Processing

  • Lim, O-Kaung;Hong, Keum-Shik;Lee, Hyuk-Soo;Park, Eun-Ho
    • Journal of Mechanical Science and Technology
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    • v.18 no.7
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    • pp.1121-1130
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    • 2004
  • The Genetic Algorithm (GA), an optimization technique based on the theory of natural selection, has proven to be a relatively robust means of searching for global optimum. It converges to the global optimum point without auxiliary information such as differentiation of function. In the case of a complex problem, the GA involves a large population number and requires a lot of computing time. To improve the process, this research used parallel processing with several personal computers. Parallel process technique is classified into two methods according to subpopulation's size and number. One is the fine-grained method (FGM), and the other is the coarse-grained method (CGM). This study selected the CGM as a parallel process technique because the load is equally divided among several computers. The given design domain should be reduced according to the degree of feasibility, because mechanical system problems have constraints. The reduced domain is used as an initial design domain. It is consistent with the feasible domain and the infeasible domain around feasible domain boundary. This parallel process used the Message Passing Interface library.

A Study of GIS Prediction Model of Domestic Fruit Cultivation Location Changes by the Global Warming -Six Tropical and Sub-tropical Fruits- (지구온난화에 따른 국내 과수작물 재배지 변화에 대한 GIS 예측 모형 연구 -여섯 가지 열대 및 아열대 과수를 중심으로-)

  • Kwak, Tae-Sik;Ki, Jung-Hoon;Kim, Young-Eun;Jeon, Hae-Min;Kim, Shi-Jin
    • Journal of Korea Spatial Information System Society
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    • v.10 no.3
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    • pp.93-106
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    • 2008
  • For agriculture is very highly dependent on climate and weather condistions, global warming seems to have a great impact on it, including its productivity, cultivation condition, product quality, and optimum cultivation location. In this study, we adopted geographical information system (GIS) in order to investigate the changes of Korea's cultivation area which are caused by global warming, especially with the examples of such tropical and sub-tropical fruits as lemon, fig, kiwi, orange, pomegranate, and mandarin. In terms of GIS techniques, we utilized the interpolate function for temperature changes, surface analysis function for slope, and raster calculator. Currently, these fruits's cultivation areas are in Jeju island and southern part of Korea. But these areas will be expanded according as our GIS model assumes $3^{\circ}C$ and $4.5^{\circ}$ increases of average and lowest temperature by the global warming in Korea. Optimum cultivation areas of these six fruits have two patterns; one is expansion and the other is belt shape shift. From the results of the study, we call for an urgent need of Korea government's policy and farmers' reasonable responses about global warming, which will be able to give more opportunities and better foods to Korea society in general.

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Design of Probabilistic Model for Optimum Manpower Planning in R&D Department (연구개발 부문 적정인력 산정을 위한 확률적 모형설계에 관한 연구)

  • Kim, ChongMan;Ahn, JungJin;Kim, ByungSoo
    • Journal of Korean Society for Quality Management
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    • v.41 no.1
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    • pp.149-162
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    • 2013
  • Purpose: The purpose of this study was to design of a probabilistic model for optimum manpower planning in R&D department by Montecarlo simulation. Methods: We investigate the process and the requirement of manpower planning and scheduling in R&D department. The empirical distributions of necessary time and manpower for R&D projects are developed. From the empirical distributions, we can estimate a probability distribution of optimum manpower in R&D department. A simulation method of estimating the probability distribution of optimum manpower is considered. It is a useful tool for obtaining the sum, the variance and other statistics of the distributions. Results: The real industry cases are given and the properties of the model are investigated by Montecarlo Simulation. we apply the model to the research laboratory of the global company, and investigate and compensate the weak points of the model. Conclusion: The proposed model provides various and correct information such as average, variance, percentile, minimum, maximum and so on. A decision maker of a company can easily develop the future plan and the task of researchers may be allocated properly. we expect that the productivity can be improved by this study. The results of this study can be also applied to other areas including shipbuilding, construction, and consulting areas.

Optimum Global Failure Prediction Model of Inconel 600 Thin Plate with Two Parallel Through-Wall Cracks

  • Moon Seong In;Kim Young Jin;Lee Jin Ho;Song Myung Ho;Choi Young Hwan
    • Nuclear Engineering and Technology
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    • v.36 no.4
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    • pp.316-326
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    • 2004
  • The $40\%$ of wall criterion, which is generally used for the plugging of steam generator tubes, is applied only to a single crack. In a previous study, a total number of 9 failure models were proposed to estimate the local failure of the ligament between cracks, and the optimum coalescence model of multiple collinear cracks was determined among these models. It is, however known that parallel axial cracks are more frequently detected than collinear axial cracks during an in-service inspection. The objective of this study is to determine the plastic collapse model that can be applied to steam generator tubes containing two parallel axial through-wall cracks. Three previously proposed local failure models were selected as the candidates. Subsequently, the interaction effects between two adjacent cracks were evaluated to screen them. Plastic collapse tests for the plate with two parallel through-wall cracks and finite element analyses were performed to determine the optimum plastic collapse model. By comparing the test results with the prediction results obtained from the candidate models, a COD base model was selected as an optimum model.

Learning and Propagation Framework of Bayesian Network using Meta-Heuristics and EM algorithm considering Dynamic Environments (EM 알고리즘 및 메타휴리스틱을 통한 다이나믹 환경에서의 베이지안 네트워크 학습 전파 프레임웍)

  • Choo, Sanghyun;Lee, Hyunsoo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.5
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    • pp.335-342
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    • 2016
  • When dynamics changes occurred in an existing Bayesian Network (BN), the related parameters embedding on the BN have to be updated to new parameters adapting to changed patterns. In this case, these parameters have to be updated with the consideration of the causalities in the BN. This research suggests a framework for updating parameters dynamically using Expectation Maximization (EM) algorithm and Harmony Search (HS) algorithm among several Meta-Heuristics techniques. While EM is an effective algorithm for estimating hidden parameters, it has a limitation that the generated solution converges a local optimum in usual. In order to overcome the limitation, this paper applies HS for tracking the global optimum values of Maximum Likelihood Estimators (MLE) of parameters. The proposed method suggests a learning and propagation framework of BN with dynamic changes for overcoming disadvantages of EM algorithm and converging a global optimum value of MLE of parameters.