• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.137-145
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• 2020

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.66-78
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• 2012

This paper proposes a computation model of the quantity supplied to optimize inventory costs for the fast fashion. The model is based on a forecasting, a store and production capacity, an assortment planning and quick response model for fast fashion retailers, respectively. It is critical to develop a standardized business process and mathematical model to respond market trends and customer requirements in the fast fashion industry. Thus, we define a product supply model that consists of forecasting, assortment plan, store capacity plan based on the visual merchandising, and production capacity plan considering quick response of the fast fashion retailers. For the forecasting, the decomposition method and multiple regression model are applied. In order to optimize inventory costs. A heuristic algorithm for the quantity supplied is designed based on the assortment plan, store capacity plan and production capacity plan. It is shown that the heuristic algorithm produces a feasible solution which outperforms the average inventory cost of a global fast fashion company.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.134-146
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• 2011

This paper suggests the product supply process model based on the store and production capacity, assortment planning and quick response for fast fashion retailers with BPMN. In the fast fashion industry, the standardized business process model is required to respond quickly market trends and customer requirements based on the quantitative and qualitative criteria. Thus we define the product supply processes which incorporate forecasting and assortment plan, cost and profitability of the production, store capacity based on the visual merchandising, and production capacity of the fast fashion retailers. Also we design the key performance indicators to evaluate the effectiveness of these product supply processes. The product supply process model for the fast fashion has great significance in embracing the fast fashion product development process because it presents the holistic view of the product supply process of the fast fashion and provides a performance evaluation mechanism. A case study shows that adopting the processes, a Korean fast fashion company achieves improvement in various performance indicators.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.54 no.3
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• pp.217-223
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• 2018

Overfishing capacity has become a global issue due to over-exploitation of fisheries resources, which result from excessive fishing intensity since the 1980s. In the case of Korea, the fishing effort has been quantified and used as an quantified index of fishing intensity. Fisheries resources of coastal fisheries in the Korean waters of the East Sea tend to decrease productivity due to deterioration in the quality of ecosystem, which result from the excessive overfishing activities according to the development of fishing gear and engine performance of vessels. In order to manage sustainable and reasonable fisheries resources, it is important to understand the fluctuation of biomass and predict the future biomass. Therefore, in this study, we forecasted biomass in the Korean waters of the East Sea for the next two decades (2017~2036) according to the changes in fishing intensity using four fishing effort scenarios; $f_{current}$, $f_{PY}$, $0.5{\times}f_{current}$ and $1.5{\times}f_{current}$. For forecasting biomass in the Korean waters of the East Sea, parameters such as exploitable carrying capacity (ECC), intrinsic rate of natural increase (r) and catchability (q) estimated by maximum entropy (ME) model was utilized and logistic function was used. In addition, coefficient of variation (CV) by the Jackknife re-sampling method was used for estimation of coefficient of variation about exploitable carrying capacity ($CV_{ECC}$). As a result, future biomass can be fluctuated below the $B_{PY}$ level when the current level of fishing effort in 2016 maintains. The results of this study are expected to be utilized as useful data to suggest direction of establishment of fisheries resources management plan for sustainable use of fisheries resources in the future.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.51-63
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• 1992

It is commonly accepted that the demand forecasting data play a vital role in deciding strategic variables such as the optimal market entry time, the price structure and the production capacity etc. In case of the new product, however, it is hard to apply the well known regression-type methodologies. In this study, we survey the characteristics of various types of new product demand forecasting(NPDF) methodologies which are useful in case the historical data are not available. Further, we explore the possibility of incorporating the NPDF methodologies and develope the unified infra-structure of the NPDF methodologies. Finally we propose an integrated prototype of the NPDF model.

• Journal of Korea Port Economic Association
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• v.24 no.3
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• pp.57-77
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• 2008

The aim of this paper is to make projection of the demand for export loaded container throughput originating at Incheon port in Korea over the period in question. Systematic analysis is used as a forecasting method instead of quantitative analysis. First of all, the method explores coincident indicators which may reflect the square measure of neighboring industrial complexes which originate/destinate general cargo in export traffic trends. It is noted that in terms of the export loaded container throughput, per unit production scale is intermediated transforming from square measure of production facilities to freight weight in Korea. Consequently, the future progress of the volume can be anticipated relying on the development schemes for developing square measure out of the total square of the industrial complexes. Thus, moving-into percentage of the industrial complexes, percentage of business categories, percentage of capacity and percentage of passing through via Incheon port are adopted and the future traffic demand is projected taking advantage of them.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.95-101
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• 2002

This paper illustrates a new fuzzy effective load model for probabilistic and fuzzy production cost simulation of the load point of the composite power system. A model for reliability evaluation of a transmission system using the fuzzy set theory is proposed for considering the flexibility or ambiguity of capacity limitation and overload of transmission lines, which are subjective matter characteristics. A conventional probabilistic approach was also used to model the uncertainties related to the objective matters for forced outage rates of generators and transmission lines in the new model. The methodology is formulated in order to consider the flexibility or ambiguity of load forecasting as well as capacity limitation and overload of transmission lines. It is expected that the Fuzzy CMELDC (CoMposite power system Effective Load Duration Curve) proposed in this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems in a competitive environment in the future. The characteristics of this new model are illustrated by some case studies of a very simple test system.

• IE interfaces
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• v.25 no.4
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• pp.441-449
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• 2012

Solar PV(photovoltaic) is paid great attention to as a possible renewable energy source to overcome recent global energy crisis. However to be a viable alternative energy source compared with fossil fuel, its market competitiveness should be attained. Grid parity is one of effective measure of market competitiveness of renewable energy. In this paper, we forecast the grid parity timing of solar PV energy in Korea using two factor learning curve model. Two factors considered in the present model are production capacity and technological improvement. As a result, it is forecasted that the grid parity will be achieved in 2019 in Korea.

• 한국정보디스플레이학회:학술대회논문집
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• 2001.08a
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• pp.9-12
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• 2001

With the explosive growth of Note-PC and Desktop monitor market, TFT LCD market confronted a entire supply shortage during 1999. Forecasting a more booming stage for the next several years, many TFT-LCD panel manufacturers continue to expand the capacity of their existing plants and also make an additional investment in building new plants. The new investment is concentrated on the $4^{th}$ generation TFT LCD line in order to improve investment efficiency. The set up of the Samsung's Gen 3.5 line progressed with satisfactorily performance using $600{\times}720mm$ glass size. We have continuously reviewed several issues regarding the glass size for our next Gen. 4 line, which leads to adopt $730{\times}920mm$. Due to the continuous enlargement of a substrate size and following difficulty in transferring cassettes, the next line is expected to be the last line that employs "cassette transfer". The layout of the next line will shift from conventional "concentration-type" to "separation-type" configuration for the purpose of reducing transfer distance as well as transfer time. The details will be discussed in this paper.