• 한국경영과학회지
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• 제21권2호
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• pp.17-33
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• 1996

Automatic transfer defined as an integrated system with a number of workstations, interstation storage buffers, automatic device and a control system, play a major role in ass production systems. Due to high capital investment needed for an automatic transferline, greater care should be taken in its design so as to maximize the system performance. One may to control the system performance is to control buffer storage. To control the interstation work-in-process inventory, we propose dual limit switches which control the buffer storage with two parameters, R and r. Under the policy, proceding station is forced down when the inventory level in the buffer reaches R until the level falls to r. For the model developed, we analyze the system characteristics and find the optimal control parameters with a serach procedure.

• 대한조선학회 특별논문집
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• 대한조선학회 2013년도 특별논문집
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• pp.35-41
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• 2013

Nowadays, automated modeling system for steel margin based on interactive user interface has been developed and applied to the production design stage. The system could increase design efficiency and minimize human error owing to recent CAD technique. However, there has been no approach to the pre-nesting design stage at all in early modeling process especially where ship model should be handled at more than two design stages using AVEVA Marine. A designer of the design stage needs artificial intelligence system beyond modeling automation when 3D model must be prepared in early modeling process using AVEVA Marine because they have focused on 2D nesting traditionally. In addition, they have a hard time figuring out the model prepared in previous design stage and modifying the model for steel purchase size in early modeling process. In this paper, artificial intelligence modeling system for automated application of steel margin in early modeling process using AVEVA Marine is developed in order to apply to the pre-nesting design stage that can detect effective segments before a calculation to find if a segment locates near block butt boundaries by filtering noise segments among lines, curves and surface intersections based on IT big data analysis.

• Industrial Engineering and Management Systems
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• 제13권3호
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• pp.304-318
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• 2014

It is necessary for a retailer to improve responsiveness to uncertain customer demand in product sales. In order to solve this problem, this paper discusses an optimal operation for a 2-stage-ordering-production system consisting of a retailer and a manufacturer. First, based on the demand information estimated at first order time $t_1$, the retailer determines the optimal initial order quantity $Q^*_1$, the optimal advertising cost $a^*_1$ and the optimal retail price $p^*_1$ of a single product at $t_1$, and then the manufacturer produces $Q^*_1$. Next, the retailer updates the demand information at second order time $t_2$. If the retailer finds that $Q^*_1$ dissatisfies the demand indicated by the demand information updated at $t_2$, the retailer determines the optimal second order quantity $Q^*_2$ under $Q^*_1$ and adjusts optimally the advertising cost and the retail price to $a^*_2$ and $p^*_2$ at $t_2$. Here, decision-making approaches for two situations are made-a decentralized supply chain (DSC) whose objective is to maximize the retailer's profit and an integrated supply chain (ISC) whose objective is to maximize the whole system's profit. In the numerical analysis, the results of the optimal decisions under DSC are compared with those under ISC. In addition, supply chain coordination is discussed to adjust the unit wholesale price at each order time as Nash Bargaining solutions.

• 한국자동차공학회논문집
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• 제19권4호
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• pp.91-98
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• 2011

Minimizing the cylinder wear and the consumption rate of cylinder oil in a large two-stroke diesel engine is of great economic importance. A motor-driven cylinder lubricator for Sulzer RT-flex large two-stroke diesel engines developed by authors is in need of mounting a quill system to lubricate cylinder parts for smoother operation. In order to apply the common-rail lubricating system to the developed cylinder lubricator as the second research stage, the quill system with a progressively quantitative distributor is improved in the electronically controlled quill system with an accumulating distributor. In this study, the effects of lubricator motor speed, plunger stroke and cylinder back pressure on oil feed rate, maximum discharge and delivery pressures are experimentally investigated by using the electronically controlled quill system with an accumulating distributor in the developed cylinder lubricator. It is found that the oil feed rate of the electronically controlled quill system with an accumulating distributor is larger than that of the quill system with a progressively quantitative distributor because of the increase of delivery speed and volume by changing the location of accumulator in the same experimental condition.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 추계학술대회 논문집 전력기술부문
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• pp.19-21
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• 2008

Renewable energy resources such as wind, wave, solar, micro hydro, tidal and biomass etc. are becoming importance stage by stage because of considering effect of the environment. Solar energy is one of the most successful sources of renewable energy for the production of electrical energy following wind energy. And, the solar/photovoltaic cell generators can not make two-state model as conventional generators, but should be modeled as multi-state model due to solar radiation random variation. The method of obtaining reliability evaluation index of solar cell generators is different from the conventional generators. This paper presents a basic study on reliability evaluation of power system considering solar cell generators with multi-states.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.271-272
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• 2008

Renewable energy resources such as wind, wave, solar, micro hydro, tidal and biomass etc are becoming important stage by stage, considering the effect of environment. Wind energy is one of the most successful sources of renewable energy for the production of electrical energy. What's more, due to wind speed random variation the wind turbine generators can not make two-state model as conventional generators. The method of obtaining reliability evaluation indices of wind turbine generators is different from the conventional generators. This paper presents a study on the reliability evaluation of power system considering wind turbine generators with a simplified multi-state model.

• ALGAE
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• 제31권3호
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• pp.267-276
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• 2016

Microalgae are currently a very promising source of biomass and triacylglycerol (TAG) for biofuels. In a previous study, we identified Chlorella saccharophila as a suitable source of oil for biodiesel production because it showed high biomass and lipid content with an appropriate fatty acid methyl esters profile. To improve the TAG accumulation in C. saccharophila, in this study we evaluated the effect of abscisic acid (ABA) addition on cell concentration, lipid content and TAG production in this microalga. First, we evaluated the effects of four ABA concentrations (1, 4, 10, and 20 μM) added at the beginning of a single-stage cultivation strategy, and found that all concentrations tested significantly increased cell concentration and TAG content in C. saccharophila. We then evaluated the addition of 1 μM ABA during the second stage of a two-stage cultivation strategy and compared it with a nitrogen deficiency treatment (ND) and a combination of ND and ABA (ND + ABA). Although ABA alone significantly increased lipid and TAG contents compared with the control, ND showed significantly higher TAG content, and ND + ABA showed the highest TAG content. When comparing the results of both strategies, we found a superior response in terms of TAG accumulation with the addition of 1 μM ABA at the beginning of a single-stage cultivation system. This strategy is a simple and effective way to improve the TAG content in C. saccharophila and probably other microalgae as a feedstock for biodiesel production.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2001년도 춘계학술대회
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• pp.77-81
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• 2001

Burn-in is a test procedure to find and eliminate the inherent initial failure of a product during or at the final stage of production process. Software testing is the validation and verification process which is used to cut off the faults from a software. The two have the common function and objective of "debugging". This article summarizes some significant models on the optimal hardware and software burn-in time, and provides the relevant paper lists. The need for the development of the unified burn-in policy of a hardware-software system is addressed.addressed.

• 대한산업공학회지
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• 제11권2호
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• pp.1-9
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• 1985

In this study, two stage transfer line with limited repair capability is modeled to formulate optimal dynamic repair priority policy. The method of Markov Chains is used to analyze the analytical model of this line. An efficient algorithm is developed, utilizing the block tridiagonal structure of the transition probability matrix, to obtain the steady state probabilities and system performance measures, such as the steady state production rate of the line and the average in-process inventory in the interstage buffer.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.80-80
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• 2022

Estimation of heading date of paddy rice is laborious and time consuming. Therefore, automatic estimation of heading date of paddy rice is highly essential. In this experiment, deep learning classification models were used to classify two difference categories of rice (vegetative and reproductive stage) based on the panicle initiation of paddy field. Specifically, the dataset includes 444 slanted view images belonging to two categories and was then expanded to include 1,497 images via IMGAUG data augmentation technique. We adopt two transfer learning strategies: (First, used transferring model weights already trained on ImageNet to six classification network models: VGGNet, ResNet, DenseNet, InceptionV3, Xception and MobileNet, Second, fine-tuned some layers of the network according to our dataset). After training the CNN model, we used several evaluation metrics commonly used for classification tasks, including Accuracy, Precision, Recall, and F1-score. In addition, GradCAM was used to generate visual explanations for each image patch. Experimental results showed that the InceptionV3 is the best performing model in terms of the accuracy, average recall, precision, and F1-score. The fine-tuned InceptionV3 model achieved an overall classification accuracy of 0.95 with a high F1-score of 0.95. Our CNN model also represented the change of rice heading date under different date of transplanting. This study demonstrated that image based deep learning model can reliably be used as an automatic monitoring system to detect the heading date of rice crops using CCTV camera.