• 한국경영과학회지
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• 제9권2호
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• pp.15-22
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• 1984

A deterministic multiproduct, facility-in series multiperiod production planning model is analyzed, where each period demand for the product of a facility appear in a fixed proportion of that for the product of the immediately following facility. The model considers concave production and inventory costs, which can depend upon the production in different facilities. No backlogging is allowed. It is shown that the model is represented via a single source network, which facilitates development of efficient dynamic programming algorithms for computing the optimal production schedule.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권5호
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• pp.496-510
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• 2016

Simulation technology is a type of shipbuilding product lifecycle management solution used to support production planning or decision-making. Normally, most shipbuilding processes are consisted of job shop production, and the modeling and simulation require professional skills and experience on shipbuilding. For these reasons, many shipbuilding companies have difficulties adapting simulation systems, regardless of the necessity for the technology. In this paper, the data model for shipyard production simulation model generation was defined by analyzing the iterative simulation modeling procedure. The shipyard production simulation data model defined in this study contains the information necessary for the conventional simulation modeling procedure and can serve as a basis for simulation model generation. The efficacy of the developed system was validated by applying it to the simulation model generation of the panel block production line. By implementing the initial simulation model generation process, which was performed in the past with a simulation modeler, the proposed system substantially reduced the modeling time. In addition, by reducing the difficulties posed by different modeler-dependent generation methods, the proposed system makes the standardization of the simulation model quality possible.

• 한국경영과학회지
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• 제1권1호
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• Asian-Australasian Journal of Animal Sciences
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• 제3권3호
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• pp.205-218
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• 1990

A general model was developed to simulate cattle growth and beef production. The present model was constructed, based on ARC metabolizable energy system in principle, and incorporated up-to-date knowledge and information into previous models, which were reported by Sanders and Cartwright (1979a,b) and Kahn (1982). The model may apply to cover a wide range of genetic and environmental conditions, because many factors relating to cattle growth and beef production are taken into consideration. The model may provide better understanding of various components and processes of beef cattle production systems.

• 한국수소및신에너지학회논문집
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• 제35권2호
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• pp.129-139
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• 2024

The significance of hydrogen economy and production technology is steadily increasing. This research reviewed strategies for utilizing hydrogen production technology by combining a multi-layer model, strategic niche management, and the need factor for Hoship. The model was validated as a strategy considering hydrogen production technology and the transformation of the energy system. Using this, a new business model for hydrogen production technology was created, finding a strategic niche and sophisticating the technology. It also proposed ways to unlock the potential of hydrogen production technology and improve its efficiency. This work contributes to the commercialization of hydrogen production technology and its role in sustainable energy conversion. It proposes a new and effective approach for utilizing hydrogen production technology, going beyond its limitations to suggest a more efficient method. It is hoped that these results will be helpful to researchers in hydrogen energy, and serve as a reference for establishing ways to utilize hydrogen production technology.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.114-117
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• 2006

One of the most important tasks of ocean color observations is to determine the distribution of phytoplankton primary production. A variety of bio-optical algorithms have been developed estimate primary production from these parameters. In this communication, we investigated the possibility of using a novel universal approximator-support vector machines (SVMs)-as the nonlinear transfer function between oceanic primary production and the information that can be directly retrieved from satellite data. The VGPM (Vertically Generalized Production Model) dataset was used to evaluate the proposed approach. The PPARR2 (Primary Production Algorithm Round Robin 2) dataset was used to further compare the precision between the VGPM model and the SVM model. Using this SVM model to calculate the global ocean primary production, the result is 45.5 PgC $yr^{-1}$, which is a little higher than the VGPM result.

• 대한산업공학회지
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• 제39권4호
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• pp.278-289
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• 2013

Up-to-date market dynamics and intense competition have forced a production system to be more widely distributed and decentralized than ever, and the production system itself can be regarded as a collaborative network of autonomous production resources in which the responsibility of decision making is also decentralized into individual autonomous entities. The conventional resource management models, however, are not suitable for the distributed and decentralized environment because of their centralized nature. In this paper, an agent-based resource management model is proposed. The proposed model applies employment relation-driven fractal organization (FrOrg) into organizational model for distributed production resources and presents a resource management framework based on employment contracts. The fractal organization is a structured association in which a self-similar pattern recursively appears, and employment relations between production resources are recursively constructed throughout the entire production system.

• 한국수산과학회지
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• 제42권5호
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• pp.494-502
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• 2009

A quantitative model was developed in order to estimate fishery production damage due to anthropogenically induced environmental changes. The model is described in the following equation, $Y_D=\frac{{\phi}_D}{{\phi}_G}[Y_0{\cdot}(t_p-t_0)-\frac{Y_0}{{\phi}_G}(1-e^{-{\phi}_G(t_p-t_0)})]$, where, $Y_D$ is annual amount of fishery production by nuclear power plant. ${\varphi}$ D and ${\varphi}$ G are instantaneous decreasing coefficient of fishery production by nuclear power plant and instantaneous decreasing coefficient of gross fishery production, respectively. $Y_0$ is annual mean fishery production without damages. $t_p$ is the present time, and $t_0$ is the starting time of damages. The model was applied to fishing grounds near a nuclear power plant on the east coast of Korea. Since fishery production damages have become bigger with increasing emission of thermal effluents from generators activities in the power plant, this factor has also been considered as, $\delta_{D_i}=\delta_D\({\sum}\limits_{i=0}^{n}\;W_i/W_T\)$, where, $\delta_{Di}$ is the cumulative damage rate in fishery production from generators, $\delta_D$ is the total cumulative damage rate in fishery production, $W_i$ is the emission amount of thermal effluents by generator i, and n is the number of generators in the nuclear power plant. This model can be used to conduct initial estimates of fishery production damages, before more detailed assessments are undertaken.

• 지질공학
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• 제29권4호
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• pp.367-381
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• 2019

We investigate pore pressure conditions and reservoir compaction associated with oil and gas production using 3 different permeability models, which are all based on one-dimensional radial flow diffusion model, but differ in considering permeability evolution during production. Model 1 assumes the most simplistic constant and invariable permeability regardless of production; Model 2 considers permeability reduction associated with reservoir compaction only due to pore pressure drawdown during production; Model 3 also considers permeability reduction but due to the effects of both pore pressure drawdown and coupled pore pressure-stress process. We first derive a unified stress-permeability relation that can be used for various sandstones. We then apply this equation to calculate pore pressure and permeability changes in the reservoir due to fluid extraction using the three permeability models. All the three models yield pore pressure profiles in the form of pressure funnel with different amounts of drawdown. Model 1, assuming constant permeability, obviously predicts the least amount of drawdown with pore pressure condition highest among the three models investigated. Model 2 estimates the largest amount of drawdown and lowest pore pressure condition. Model 3 shows slightly higher pore pressure condition than Model 2 because stress-pore pressure coupling process reduces the effective stress increase due to pore pressure depletion. We compare field data of production rate with the results of the three models. While models 1 and 2 respectively overestimates and underestimates the production rate, Model 3 estimates the field data fairly well. Our result affirms that coupling process between stress and pore pressure occurs during production, and that it is important to incorporate the coupling process in the permeability modeling, especially for tight reservoir having low permeability.

• 대한산업공학회지
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• 제40권3호
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.