• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.110-117
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• 2012

The demand for facility used in producing multi-products is changed dynamically for discrete and finite time periods. The excess or the shortage for facility is occurred according to difference of the facility capacity size and demand for facility through given time periods. The shortage facility is met through the outsourcing production. The excess facility cost is considered for the periods that the facility capacity is greater than the demand for the facility, and the outsourcing production cost is considered for the periods that the demand for facility is greater than the facility capacity. This paper addresses to determine the facility capacity size, outsourcing production products and amount that minimizes the sum of the facility capacity cost, the excess facility cost and the outsourcing production cost. The characteristics of the optimal solution are analyzed, and an algorithm applying them is developed. A numerical example is shown to explain the problem.

• Journal of the Korea Society for Simulation
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• v.12 no.1
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• pp.35-48
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• 2003

This paper suggests the long-term strategy of the production distribution planning considering the capacity of factory production and the uncertain demand in a supply chain. This paper determines the near optimal capacity of factory production by using the advantages of mathematical and simulation models. Also, the relationship between the capacity from the suggested model and the strategy of production and distribution in a supply chain is studied. Arena is used for modeling and analysis.

• 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 the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.59-65
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• 1988

This paper discusses the problem of coordinating aggregate planning and production schedules, minimizing the combined set-up inventory and capacity costs. In this study, by using the relation of fixed production quantity and the number of set-up we develop a heuristirc procedure of solving the discrete demand, fixed production quantity, variable capacity problem. First, we obtain the trade-off between set-up cost and capacity cost, then search the point minimizing the combined inventory and capacity costs.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.111-122
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• 2012

Capacity planning plays an important role not only for master production plan but also for facility or layout design in shipbuilding. Product work breakdown structure, attributes of production resources, and production method or process data are associated in order to make the discrete event simulation model of shipyard layout plan. The production amount of each process and the process time is assumed to be stochastic. Based on the stochastic discrete event simulation model, the production capacity of each facility in shipyard is estimated. The stochastic model of product arrival time, process time and transferring time is introduced for each process. Also, the production capacity is estimated for the assumed master production schedule.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.179-184
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• 2005

An accurate evaluation of a production capacity is an important role for production planning in manufacturing industry. The study has been partly done about the fluctuation in the conventional study of the production capacity, but the study of the subordination has been hardly done. Therefore, in this paper, we will devide by the production capacity which is formed into the production subjects to evaluate objectively the differences of between the actual capacity and the designed capacity in manufacturing industry and will suggest production capacity estimation model which is considered the fluctuation and the subordination, the decreasing causes of the production capacity. The weight of fluctuation which is used for the computation of the ratio of fluctuation and the ratio of subordination and the subordination are denoted to the interval number Thus, the production capacity is denoted to the interval numbers. The efficiency of the proposed model will show through the case study.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.5
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• pp.471-476
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• 1995

The relationship between udder maximum capacity (36-h accumulated milk yield) and the response of dairy cows (average producers) to thrice-daily milking was studied in 25 Friesian and 15 Jersey cows using the technique of half-udder study. Maximum half-udder capacity (acual yield) as well as whole udder capacity (estimated by udder measurements) was not altered significantly after 12-day thrice-daily milking period compared with a similar twice-daily period, although there was a positive response to increased milking frequency on secretion rate during this period. No effect of breed, season of the year or stage of lactation was observed on the above relationship. Hours-worth of capacity was higher with increased milking frequency, with Jersey than Friesian. These results suggest that udder capacity is not a limiting factor in increased milk production.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.165-173
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• 2000

Analytic models have been developed to solve integrated production-distribution problems in supply chain management (SCM). As one of major constraints in analytic models, capacity, which is the total operation time in this paper has mostly been known or disregarded assuming infinite capacity. Also, as major factors, machine processing time to fabricate or assemble a part or product at a certain machine center in production system and vehicle processing time to deliver a product to a customer by a certain vehicle in distribution system have been fixed and regarded as a static factor, But in the real systems significant differences exit between capacity and the required time to achieve the production-distribution plan and between processing time and consumed time to process a part or product. In this paper, capacity and processing times in the analytic model are considered as dynamic factors and adjusted by the results from independently developed simulation model, which includes general production-distribution characteristics. Through experiments, we obtain the more realistic solutions reflecting stochastic natures by performing the iterative analytic-simulation procedure.

• Transactions of the Korean hydrogen and new energy society
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• v.32 no.6
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• pp.477-482
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• 2021

Hydrogen production, hydrogen production cost, and utilization rate were calculated assuming four cases of hydrogen production system in combination of photovoltaic power generation (PV), water electrolysis system (WE), battery energy storage system (BESS), and power grid. In the case of using the PV and WE in direct connection, the smaller the capacity of the WE, the higher the capacity factor rate and the lower the hydrogen production cost. When PV and WE are directly connected, hydrogen production occurs intermittently according to time zones and seasons. In addition to the connection of PV and WE, if BESS and power grid connection are added, the capacity factor of WE can be 100%, and stable hydrogen production is possible. If BESS is additionally installed, hydrogen production cost increases due to increase in Capital Expenditures, and Operating Expenditure also increases slightly due to charging and discharging loss. Even in a hydrogen production system that connects PV and WE, linking with power grid is advantageous in terms of stable hydrogen production and improvement of capacity factor.

• IE interfaces
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• v.22 no.1
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• pp.1-9
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• 2009

As the LCD fabrication factories (Fab) are highly capital-intensive and the markets are very competitive, it is an essential requirement of operational management to achieve full-capacity production while meeting customer demands on time. In a typical LCD Fab, medium-term schedules such as release plans and production plans are critical to achieve the goal of full-capacity production and on-time delivery. Presented in this paper is a framework for weekly planning system generating medium-term schedules using a finite-capacity planning method. Also this paper presents a release planning method applying capacityfiltering algorithm, especially backward capacity-filtering procedure, which is one of the finite-capacity planning methods. In addition, performance analyses using actual data of a TFT-LCD Fab show that the proposed method is superior to existing methods or commercial S/W products generating release plans.