• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.65-68
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• 2001

Short shot is a molded part that is incomplete since insufficient material was injected into the mold. Remedial actions to solve short shot can be done by injection molding experts based on their empirical knowledge. Modifying mold and part, changing resin to less viscous one, and adjusting process conditions are general remedies. Experts of injection molding might try to adjust process conditions such as mold temperature, melt temperature, injection time based on their empirical knowledge as the first remedy because adjustment of process conditions is the most economic way in time and cost. However it is difficult to find appropriate process conditions as they are highly coupled and there are so many elements to be considered. In this paper, a fuzzy logic algorithm has been proposed to find an appropriate mold temperature. With the percentage of the insufficient Quantity of an injection molded part, an appropriate mold temperature can be obtained by the fuzzy logic algorithm.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.369-382
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• 2014

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end-product, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the re-implementation of the model for future development and case studies.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.242-244
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• 2000

This paper presents a method for real-time estimation of TCSC quantity in order to enhance the power system transient stability energy margin using fuzzy neural network in multi-machine system. This paper has two parts, the first part is to estimate the energy margin. To set critical energy, we use the potential energy boundary surface(PEBS) method which one of the transient energy function(TEF) method. And the second is to determine the TCSC quantify and the line to be injected. In order to make training data in this step, we use genetic algorithm. The proposed method is applied to 6-bus, 7-line, 4-machine model system to show its effectiveness.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.3
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• pp.538-545
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• 1995

The heat transfer model of ondol heating system is derived in the linear form. The step responses of On-Off controller, PID controller and Position type fuzzy controllers are compared in the sense of several aspects : variation of temperature feedback variable, variation of supplied heat quantity by the boiler, variation of flow rate, variation of thickness of the base, variation of the outdoor temperature.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.83-86
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• 2001

In injection molding, short shot is one of the frequent and fatal defects. Experts of injection molding usually adjust process conditions such as injection time, mold temperature, and melt temperature because it is the most economic way in time and cost. However it is a difficult task to find appropriate process conditions for troubleshooting of short shot as injection molding process is a highly nonlinear system and process conditions are coupled. In this paper, a fuzzy neural network(FNN) has been applied to injection molding process to shorten troubleshooting time of short shot. Based on melt temperature and fill time, a reasonable initial mold temperature is recommended by the FNN, and then the mold temperature is inputted to injection molding process. Depending on injection molding result, specifically the insufficient quantity of an injection molded part, an appropriate mold temperature is recommend repeatedly through the FNN.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.531-536
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• 2014

With the very large quantity of information available on the Internet, techniques for dealing with the abundance of documents have become increasingly necessary but the problem of processing information in the documents is still technically challenging and remains under study. Automatic document summary techniques have been considered as one of critical solutions for processing documents to retain the important points and to remove duplicated contents of the original documents. In this paper, we propose a document summarization technique that uses a fuzzy theory. Proposed summary technique solves the ambiguous problem of various features determining the importance of the sentence and the experiment result shows that the technique generates better results than other previous techniques.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.107-118
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• 1993

Continuous increasing of impervious area due to urbanization and rainfall quantity due to environmental changes aggravate flooding risk in low land area. Therefore. Seoul municipal authorities go on securing an ample budget for reinforcement and establishment of inner water and inland drainage pumping facilities. But. there is no investment for developing optimal operation rules for appropriate application of existing facilities. In this study. fuzzy control techniques are developed. and applied to 57 stations of inner water and inland drainage pump for model assessment. In these results. fuzzy models have more efficiency in the inland flooding protection than the existing pump operation rule by water level in the same conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.58-64
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• 1997

FLC(Fuzzy Logic Controller) is stronger to the disturbance than a classical controller and its overshoot of the intialized value is excellent. In case an unknown process or the mathematical modeling of a complicated system is impossible, a fit control quantity can be acquired by the Fuzzy inference. But FLC can not converge correctly to the desirable value because the FLC's output value by the size of the quantization level of the Fuzzy variable always has a minor error. There are many ways to eliminate the minor error, but I will suggest GA-FLC and EP-FLC Hybrid controller which csombines FLC with GA(Genetic Algorithm) and EP(Evo1ution Programming). In this paper, the output characteristics of this Hybrid controller will be compared and analyzed with those of FLC, it will he showed that this Hybrid controller converge correctly to the desirable value without any error, and !he convergence speed performance of these two kinds of Hyhrid controller also will be compared.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.3
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• pp.535-546
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• 2000

Juam lake is a major water resource for the industrial and agricultural activities as well as the resident life of Kwangju and Chonnam area. However, the water quality of the lake is getting worse due to a large quantity of pollutant inflowing to the lake. As a preliminary step in making the countermeasure to achieve the water quality goal of the lake. it is necessary to understand how the water quality of the lake will be in future. Several computer programs can be used to predict the water quality of lake. Each of these programs requires a number of input data such as hydrological and meteorological data. and the quantity of the pollutant inflowed. but some or most of the input data contain uncertainty. which eventually results in the uncertainty of prediction value (future level of water quality). Generally. the uncetainty stems from the lack of information available. the randomness of future situation. and the incomplete knowledge of expert. Thus. the purpose of this study is to present a method for representing the degree of the uncertainty contained in input data by applying fuzzy theory and incorporating it directly into the water quality modeling process. By using the method. the prediction on the future water quality level of Juam lake can be made that is more appropriate and realistic than the one made without taking uncertainty in account.

• Transactions of the Korean hydrogen and new energy society
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• v.20 no.1
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• pp.22-30
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• 2009

Energy environment has been changing rapidly such as the fluctuation of oil prices and the effect on UNFCCC. Oil price change affects Korea's economy heavily due to her poor natural resources and large dependence of consumed energy resources. Korea takes the 4th place of importing the crude oil and 9th place in $CO_2$ emissions with the 1st place of $CO_2$ emissions increasing rate. Considering the current statue of Korea including oil price change and UNFCCC, Korea will be expected to be the Annex I nation due to Korean energy environments and the quantity of $CO_2$ emission. Energy technology development is a crucial key to cope with Korea's national energy security and environments. In this study, we establish the framework, which allocates the relative weights of assessment criteria and sub-criteria, for assessing and selecting R&D programs of energy technologies strategically. We integrated fuzzy theory and analytic hierarchy process (AHP) approach since the fuzzy AHP approach reflects the vagueness of human thoughts and perception effectively as making pairwise comparisons of criteria and alternatives. The fundamental data of this research results will support R&D planning phase for policy-makers and the production of well focused R&D outcomes.