• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.138-149
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• 2016

Quality function deployment (QFD) is a widely adopted customer-oriented product development methodology by translating customer requirements (CRs) into technical attributes (TAs), and subsequently into parts characteristics, process plans, and manufacturing operations. A main activity in QFD planning process is the determination of the target levels of TAs of a product so as to achieve a high level of customer satisfaction using the data or information included in the houses of quality (HoQ). Gathering the information or data for a HoQ may involve various inputs in the form of linguistic data which are inherently vague, or human perception, judgement and evaluation for the information and data. This research focuses on how to deal with this kind of impreciseness in QFD optimization. In this paper, it is assumed as more realistic situation that the values of TAs are taken as discrete, which means each TA has a few alternatives, as well as the customer satisfaction level acquired by each alternative of TAs and related cost are determined based on subjective or imprecise information and/or data. To handle these imprecise information and/or data, an approach using some basic definitions of fuzzy sets and the signed distance method for ranking fuzzy numbers is proposed. An example of a washing machine under two-segment market is provided for illustrating the proposed approach, and in this example, the difference between the optimal solution from the fuzzy model and that from the crisp model is compared as well as the advantage of using the fuzzy model is drawn.

• Journal of Navigation and Port Research
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• v.33 no.6
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• pp.387-393
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• 2009

In this paper, a 3-D simulator was developed to estimate visually the performance of propelling and integrated control system of the underwater cleaning robot. Based on the dynamics analysis of the UCR, the 3-D model of the UCR was used in the simulator in which position and velocity are included Also, an input and control system using a joystick was developed, and the simulator was applied to the input and control of the simulator. Moreover, an integrated navigation control system was designed, and its performance was validated by a way-point simulator including a PI-based fuzzy control law.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.6
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• pp.469-475
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• 2008

In this paper, control of small PEM(Proton Exchange Membrane) fuel cell stack by a microprocessor is introduced. The water management of fuel cell stack inside, a key technique in fuel cell control, can be achieved by adjusting the required air flow for fuel and cooling, and by purging the excessive water from the stack. It is very important to precisely control the BOS(Balance of Stack) since the stable operation of the fuel cell system mainly depends on it. In this study the fuel efficiency of the system is improved by the control of the system based on the measured air flow and purge cycle during the optimal operation and its effectiveness is proved by the experiments. The operating stability of the system is improved by the developed controller using a microprocessor and it is expected to be widely used for the control of small PEM fuel cell stack.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.191-198
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• 1999

Biofeedback training is one of physiological self control methods for patients who has psychological problem and rehabilitational problem. It has been used to control blood pressure, heart rate, peripheral temperature, respiration, electromyography (ENG), and other biological signals-ENG, respiration, heat rate, peripheral temperature, skin conductance level-was developed in house. We applied this system to alcohol dependent patients to perform biofeedback training. In this experiment, the relaxation biofeedback training for alcohol dependent patient was carried out and the tension state for the change of biological signals were estimated using the fuzzy theory after relaxation biofeenback training. Eight alcohol dependent patients were agreed to participate in this experiment. Result showed that 1) the tension degree of patients were higher than the tension degree of normal subject. 2) The tension degree of patients were decreased as the training numbers were increased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4A
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• pp.385-392
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• 2006

It is widely accepted that high user densities in mobile multimedia environments can only be achieved with micro- and pico-cell. The smaller cell size causes frequent handovers between cells, and decreases permissible handover processing delay. This may result in the handover failure, in addition to the loss of some packets during the handover. In these cases, re-transmission is needed in order to compensate errors, which in turn triggers a rapid degradation of throughput. In this paper, we propose a new handover scheme for the next generation mobile communication systems, in which the handover setup process is done in advance before a handover request by predicting the handover cell based on mobile terminal's current position and moving direction. Simulation is performed in order to analyze the handover failure rate and packet loss rate. Simulation results show that our proposed method provides a better performance than the conventional method.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.3-12
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• 1996

Sliding mode controller(SMC) is a simple but powerful nonlinear controller, because it guarantees the stability and the robustness. However, it leads to the high frequency chattering of the control input. Although the phenomenon can be avoided by introducing a thin boundary layer to the sliding surface, the method results in a steady state: error proportional to the boundary layer thickness. In this paper, we proposed a new sliding mode controller with self-tuning the thickness of a boundary layer. It uses a fuzzy rule base for tuning the thickness of a boundary layer. That is, the thickness is increased to some degree to reject a discontinuous control input at the initial state and then it is decreased as the states approaches to the steady states for improving the tracking performance. In order to assure the control performance, we perf'ormed the computer simulation using an inverted pendulum system as a controlled plant.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.29-37
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• 2017

This papers focuses on remanufacturing processes in a closed loop supply chain. The remanufacturing processes is considered as one of the effective strategies for enterprises' sustainability. For this reason, a lot of companies have attempted to apply remanufacturing related methods to their manufacturing processes. While many research studies focused on the return rate for remanufacturing parts as a control parameter, the relationship with demand certainties has been studied less comparatively. This paper considers a closed loop supply chain environment with remanufacturing processes, where highly fluctuating demands are embedded. While other research studies capture uncertainties using probability theories, highly fluctuating demands are modeled using a fuzzy logic based ambiguity based modeling framework. The previous studies on the remanufacturing have been limited in solving the actual supply chain management situation and issues by analyzing the various situations and variables constituting the supply chain model in a linear relationship. In order to overcome these limitations, this papers considers that the relationship between price and demand is nonlinear. In order to interpret the relationship between demand and price, a new price elasticity of demand is modeled using a fuzzy based nonlinear function and analyzed. This papers contributes to setup and to provide an effective price strategy reflecting highly demand uncertainties in the closed loop supply chain management with remanufacturing processes. Also, this papers present various procedures and analytical methods for constructing accurate parameter and membership functions that deal with extended uncertainty through fuzzy logic system based modeling rather than existing probability distribution based uncertainty modeling.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.467-472
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• 2002

In this paper, we propose a Fuzzy Cellular Neural Network(FCNN) that is based on a-Least Trimmed Square Hausdorff distance(a-LTSHD) which applies Hausdorff distance(HD) to the FCNN structure in order to remove the impulse noise of images effectively and also improve the speed of operation. FCNN incorporates Fuzzy set theory to Cellular Neural Network(CNN) structure and HD is used as a scale which computes the distance between set or two pixels in binary images without confrontation of the feature object. This method has been widely used with the adjustment of the object. For performance evaluation, our proposed method is analyzed in comparison with the conventional FCNN, with the Opening-Closing(OC) method, and the LTSHD based FCNN by using Mean Square Error(MSE) and Signal to Noise Ratio(SNR). As a result, the performance of our proposed network structure is found to be superior to the other algorithms in the removal of impulse noise.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.586-591
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• 2014

In this study, we introduce Radial Basis Function Neural Networks(RBFNNs) classifier using Artificial Bee Colony(ABC) algorithm in order to classify between precipitation event and non-precipitation event from given radar data. Input information data is rebuilt up through feature analysis of meteorological radar data used in Korea Meteorological Administration. In the condition phase of the proposed classifier, the values of fitness are obtained by using Fuzzy C-Mean clustering method, and the coefficients of polynomial function used in the conclusion phase are estimated by least square method. In the aggregation phase, the final output is obtained by using fuzzy inference method. The performance results of the proposed classifier are compared and analyzed by considering both QC(Quality control) data and CZ(corrected reflectivity) data being used in Korea Meteorological Administration.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.126-131
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• 2017

In this paper, we propose a method to extract meaningful motion among various kinds of hand gestures on giving commands to robots using hand gestures. On giving a command to the robot, the hand gestures of people can be divided into a preparation one, a main one, and a finishing one. The main motion is a meaningful one for transmitting a command to the robot in this process, and the other operation is a meaningless auxiliary operation to do the main motion. Therefore, it is necessary to extract only the main motion from the continuous hand gestures. In addition, people can move their hands unconsciously. These actions must also be judged by the robot with meaningless ones. In this study, we extract human skeleton data from a depth image obtained by using a Kinect v2 sensor and extract location data of hands data from them. By using the Kalman filter, we track the location of the hand and distinguish whether hand motion is meaningful or meaningless to recognize the hand gesture by using the hidden markov model.