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      • KCI등재

        계층적분석기법을 이용한 APS 개선방안 도출

        하정훈(Chunghun Ha),이영관(Young Kwan Lee),옥창수(Changsoo Ok) 한국산업경영시스템학회 2011 한국산업경영시스템학회지 Vol.34 No.3

        The advanced planning and scheduling(APS) is an well known enterprise information system that provides optimal production schedules and supports to complete production on time by solving the complex scheduling problems including capacity and due dates. In this paper, we focused on the improvement of the APS that is already established on a real company. The existing APS had several drawbacks, thus utilization and satisfaction were very low. We performed the focused group interviews and the process analysis and could find that the end users and developers have various objectives and the frequently used functions are different. We applied the analytical hierarchy process(AHP) to converge opinions of them on quantitative data. The results show that it is necessary to enhance visibility, to improve user interfaces and response speed, and to reconcile the real business process and the APS’s process.

      • KCI등재

        반도체에 적합한 복합 학습곡선 모형

        하정훈(Chunghun Ha) 대한산업공학회 2010 산업공학 Vol.23 No.3

        The learning curve model is a mathematical form which represents the relationship between the manufacturing experience and its effectiveness. The semiconductor manufacturing is widely known as an appropriate example for the learning effect due to its complicated manufacturing processes. In this paper, I propose a new compound learning curve model for semiconductor products in which the general learning curve model and the growth curve are composed. The dependent variable and the effective independent variables of the model were abstracted from the existing learning curve models and selected according to multiple regression processes. The simulation results using the historical DRAM data show that the proposed compound learning curve model is one of adequate models for describing learning effect of semiconductor products.

      • LCD생산시스템에서 Repair와 Rework을 고려한 수율과 원가 분석 모델

        하정훈(Chunghun Ha) 대한산업공학회 2007 대한산업공학회지 Vol.33 No.3

        The cost modeling of the LCD manufacturing system with the repair and the rework process is hard to achieve because of it’s complex manufacturing process. The technical cost modeling divides each process separately and hierarchically, so it is very useful to calculate the total manufacturing cost of the complex manufacturing system. We applied the method to the complex LCD manufacturing system to obtain more accurate cost model. Yields are the most important control parameters in manufacturing. In this paper, we propose a yield based cost model for the LCD manufacturing system and reveal the relationship between manufacturing yield and cost. Through the model, we can estimate the manufacturing cost on the basis of yields that are control indicators of manufacturing. Some simulations are performed to observe the effects of the yield to the cost, and the results are coincide with the real situation. With the proposed model, we expect to develop some optimization problems for enlarging productivity in the LCD industry.

      • KCI등재

        Markov Chain Monte Carlo를 이용한 반도체 결함 클러스터링 파라미터의 추정

        하정훈(Chunghun Ha),장준현(Jun Hyun Chang),김준현(Joon Hyun Kim) 한국산업경영시스템학회 2009 한국산업경영시스템학회지 Vol.32 No.3

        Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

      • KCI등재

        A Binomial Weighted Exponential Smoothing for Intermittent Demand Forecasting

        Chunghun Ha(하정훈) 한국산업경영시스템학회 2018 한국산업경영시스템학회지 Vol.41 No.1

        Intermittent demand is a demand with a pattern in which zero demands occur frequently and non-zero demands occur sporadically. This type of demand mainly appears in spare parts with very low demand. Croston’s method, which is an initiative intermittent demand forecasting method, estimates the average demand by separately estimating the size of non-zero demands and the interval between non-zero demands. Such smoothing type of forecasting methods can be suitable for mid-term or long-term demand forecast-ing because those provides the same demand forecasts during the forecasting horizon. However, the smoothing type of forecasting methods aims at short-term forecasting, so the estimated average forecast is a factor to decrease accuracy. In this paper, we propose a forecasting method to improve short-term accuracy by improving Croston’s method for intermittent demand forecasting. The proposed forecasting method estimates both the non-zero demand size and the zero demands’ interval separately, as in Croston’s method, but the forecast at a future period adjusted by binomial weight according to occurrence probability. This serves to improve the accuracy of short-term forecasts. In this paper, we first prove the unbiasedness of the proposed method as an important attribute in forecasting. The performance of the proposed method is compared with those of five existing forecasting methods via eight evaluation criteria. The simulation results show that the proposed forecasting method is superior to other methods in terms of all evaluation criteria in short-term forecasting regardless of average size and dispersion parameter of demands. However, the larger the average demand size and dispersion are, that is, the closer to continuous demand, the less the performance gap with other forecasting methods.

      • KCI등재

        시뮬레이션을 통한 생산흐름통제시스템의 성능비교

        박상근(Sang Geun Park),하정훈(Chunghun Ha) 한국산업경영시스템학회 2012 한국산업경영시스템학회지 Vol.35 No.1

        Material flow control mechanism is a kind of operational policy in manufacturing. It is very important because it varies throughput, throughput time, and work-in-process (WIP) under the same manufacturing resources. Many Researchers have developed various material flow control mechanisms and insisted that their mechanism is superior to others. However the experimental environment used in the performance comparison are different and impractical. In this paper, we set various manufacturing environments to fairly compare five previous material flow control mechanism : Push, Pull, CONWIP, Gated MaxWIP, and Critical WIP Loops. The simulation results show that the Push is superior to others in both of throughput and WIP if required demand is less than 80% of capacity. In addition, the performance of CONWIP and its variants are not different statistically.

      • KCI등재

        영화 흥행과 관련된 영화별 특성에 대한 군집분석 : 웹 크롤링 활용

        이재일(Jai-Ill),전영호(Lee․,Young-Ho),하정훈(Chun,Chunghun Ha) 한국산업경영시스템학회 2016 한국산업경영시스템학회지 Vol.39 No.3

        Forecasting of box office performance after a film release is very important, from the viewpoint of increase profitability by reducing the production cost and the marketing cost. Analysis of psychological factors such as word-of-mouth and expert assessment is essential, but hard to perform due to the difficulties of data collection. Information technology such as web crawling and text mining can help to overcome this situation. For effective text mining, categorization of objects is required. In this perspective, the objective of this study is to provide a framework for classifying films according to their characteristics. Data including psychological factors are collected from Web sites using the web crawling. A clustering analysis is conducted to classify films and a series of one-way ANOVA analysis are conducted to statistically verify the differences of characteristics among groups. The result of the cluster analysis based on the review and revenues shows that the films can be categorized into four distinct groups and the differences of characteristics are statistically significant. The first group is high sales of the box office and the number of clicks on reviews is higher than other groups. The characteristic of the second group is similar with the 1st group, while the length of review is longer and the box office sales are not good. The third group s audiences prefer to documentaries and animations and the number of comments and interests are significantly lower than other groups. The last group prefer to criminal, thriller and suspense genre. Correspondence analysis is also conducted to match the groups and intrinsic characteristics of films such as genre, movie rating and nation.

      • KCI등재

        순회판매원문제를 위한 분산유전알고리즘 성능평가

        김영남(Young Nam Kim),이민정(Min Jung Lee),하정훈(Chunghun Ha) 한국산업경영시스템학회 2016 한국산업경영시스템학회지 Vol.39 No.4

        Distributed genetic algorithm (DGA), also known as island model or coarse-grained model, is a kind of parallel genetic algorithm, in which a population is partitioned into several sub-populations and each of them evolves with its own genetic operators to maintain diversity of individuals. It is known that DGA is superior to conventional genetic algorithm with a single population in terms of solution quality and computation time. Several researches have been conducted to evaluate effects of parameters on GAs, but there is no research work yet that deals with structure of DGA. In this study, we tried to evaluate performance of various genetic algorithms (GAs) for the famous symmetric traveling salesman problems. The considered GAs include a conventional serial GA (SGA) with IGX (Improved Greedy Crossover) and several DGAs with various combinations of crossover operators such as OX (Order Crossover), DPX (Distance Preserving Crossover), GX (Greedy Crossover), and IGX. Two distinct immigration policies, conventional noncompetitive policy and newly proposed competitive policy are also considered. To compare performance of GAs clearly, a series of analysis of variance (ANOVA) is conducted for several scenarios. The experimental results and ANOVAs show that DGAs outperform SGA in terms of computation time, while the solution quality is statistically the same. The most effective crossover operators are revealed as IGX and DPX, especially IGX is outstanding to improve solution quality regardless of type of GAs. In the perspective of immigration policy, the proposed competitive policy is slightly superior to the conventional policy when the problem size is large.

      • KCI등재

        LNG FPSO 펌프타워 고장 예지 방안에 관한 연구

        김용재(Yongjae Kim),조상제(SangJe Cho),전홍배(Hong-Bae Jun),하정훈(Chunghun Ha),신종호(Jongho Shin) (사)한국CDE학회 2016 한국CDE학회 논문집 Vol.21 No.2

        The plant equipment usually has a long life cycle. During its O&M (Operation & Maintenance) phase, since the occurrence of an accident of offshore plant equipment causes catastrophic damage, it is necessary to make more efforts for managing critical offshore equipment. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the health status data of important offshore equipment and their environment data, which leads to much concern on CBM (Condition-Based Maintenance). In this study, we will propose an approach to estimate the remaining lifetime of an offshore plant equipment (pump tower) based on gathered ocean environment data.

      • KCI등재

        생산환경 변화에 따른 최적 Material Flow Control 선택방법

        박상근(Sang Geun Park),박성호(Sung Ho Park),하정훈(Chunghun Ha) 한국산업경영시스템학회 2013 한국산업경영시스템학회지 Vol.36 No.2

        Material flow control (MFC) is a kind of operational policy to control of the movement of raw materials, components, and products through the manufacturing lines. It is very important because it varies throughput, line cycle time, and work-in-process (WIP) under the same manufacturing environments. MFC can be largely categorized into three types such as Push, Pull, and Hybrid. In this paper, we set various manufacturing environments to compare five existing MFC mechanisms: Push, Pull, and Hybrid (CONWIP, Gated MaxWIP, Critical WIP Loops, etc). Three manufacturing environments, manufacturing policies (make to stock and make to order), demand (low, medium, high), and line balancing (balanced, unbalanced, and highly unbalanced) are considered. The MFCs are compared in the point of the five functional efficiencies and the proposed compounded efficiency. The simulation results shows that the Push is superior in the functional efficiency and GMWIP is superior in the compounded efficiency.

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