• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.328-337
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• 2004

Tool costs can comprise a significant part of the total operating costs of Flexible Manufacturing Systems. We address the problem of determining the optimal processing times of individual operations and routing mix in FMSs with multiple routes for each part type in order to minimize tool cost, subject to meeting a throughput constraint for each part type. The problem is formulated as a nonlinear program superimposed on a closed queueing network of the FMSs under consideration. Numerical examples reveal the potential of our approach for significant saving in tool costs.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.118-127
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• 1991

In this paper, criteria and algorithms for the optimal service rate in a closed queueing network have been established. The objective is to minimize total cost. It is shown that system throughput is increasing concave over the service rate of a node and cycle time is increasing convex over the set of service times with a single calss of cubsomers. This enables developing an algorithm using a steepest descent method when the cost function for service rate is convex. The efficiency of the algorithm rests on the fact that the steepest descent direction is readily obtained at each iteration from the MVA algorithm. Several numerical examples are presented. The major application of this research is optimization of facility capacity in a manufacturing system.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.175-187
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• 2004

We consider the simultaneous selection of part routes for multiple part types in Flexible Manufacturing Systems (FMSs). Using an optimization framework we investigate two alternative route assignment policies. The one, called routing mix policy in the literature, specifies the optimal proportion of each part type to be produced along its alternative routes, assuming that the proportions can be kept during execution. The other one, which we propose and call pallet allocation policy, partitions the pallets assigned to each part type among the routes. The optimization framework used is a nonlinear programming superimposed on a closed queueing network model of an FMS which produces multiple part types with distinct repeated visits to certain workstations. The objective is to maximize the weighted throughput. Our study shows that the simultaneous use of multiple routes leads to reduced bottleneck utilization, improved workload balance, and a significant increase in the FMS's weighted throughput, without any additional capital investments. Based on numerical work, we also conjecture that pallet allocation policy is more robust than routing mix policy, operationally easier to implement, and may yield higher revenues.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.153-168
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• 1998

In this study we consider a CONWIP system in which the processing times at each station follow an exponential distribution and the demands for the finished Products arrive according to a compound Poisson process. The demands that are not satisfied instantaneously are assumed to be backordered. For this system we develop an approximation method to obtain the performance measures such as steady state probabilities of the number of parts at each station, the proportion of backordered demands, the average number of backordered demands and the mean waiting time of a backordered demand. For the analysis of the proposed CONWIP system, we model the CONWIP system as a closed queueing network with a synchronization station and analyze the closed queueing network using a product form approximation method. A matrix geometric method is used to solve the subnetwork in the application of the product-form approximation method. To test the accuracy of the approximation method, the results obtained from the approximation method were compared with those obtained by simulation. Comparisons with simulation have shown that the approximate method provides fairly good results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.8-12
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• 2004

In this study we consider a CONWIP system in which the processing times at each station follow a Coxian distribution and the demands for the finished products arrive according to a compound Poisson process. The demands that are not satisfied are backordered according to the number of demands that exist at their arrival instants. For this system we develop an approximation method to calculate order based performance measures such as the mean time of fulfilling a customer order and the mean number o: customer orders. For the analysis of the proposed CONWIP system, we model the CONWIP system as a closed queueing network with a synchronization station and analyze the closed queueing network using a product form approximation method. Numerical tests show that the approximation method provides fairly good estimation of the performance measures of interest.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.2
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• pp.73-79
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• 2005

This paper is proposed hybrid artificial intelligent (HAI) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using a closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.255-262
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• 1998

This paper presents a translation, rotation and scale invariant methodology for the recognition of closed planar shape images using the bispectrum of a contour sequence and the learning vector quantization(LVQ) neural classifier. The contour sequences obtained from the closed planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The higher order spectra based on third order cumulants is applied to tihs contour sample to extract fifteen bispectral feature vectors for each planar image. There feature vector, which are invariant to shape translation, rotation and scale transformation, can be used to represent two0dimensional planar images and are fed into a neural network classifier. The LVQ architecture is chosen as a neural classifier because the network is easy and fast to train, the structure is relatively simple. The experimental recognition processes with eight different hapes of aircraft images are presented to illustrate the high performance of this proposed method even the target images are significantly corrupted by noise.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.131-135
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• 2009

This paper is the introduction of our work on distributed load scheduling in single-level tree network. In this paper, we derive a new calculation model in single-level tree network and show a closed-form formulation of the time for computation system. There are so many examples of the application of this technology such as distributed database, biology computation on genus, grid computing, numerical computing, video and audio signal processing, etc.

• Journal of Power Electronics
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• v.12 no.5
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• pp.800-812
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• 2012

This paper analyses the mathematical model and control strategies of a Hybrid Active Power Filter with Injection Circuit (IHAPF). The control strategy based on the load harmonic current detection is selected. A novel control method for a IHAPF, which is based on the analyzed control mathematical model, is proposed. It consists of two closed-control loops. The upper closed-control loop consists of a single fuzzy logic controller and the IHAPF model, while the lower closed-control loop is composed of an Adaptive Network based Fuzzy Inference System (ANFIS) controller, a Neural Generalized Predictive (NGP) regulator and the IHAPF model. The purpose of the lower closed-control loop is to improve the performance of the upper closed-control loop. When compared to other control methods, the simulation and experimental results show that the proposed control method has the advantages of a shorter response time, good online control and very effective harmonics reduction.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.300-302
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• 2006

Middleware offers function that user application program can transmit data independently of network device. Connection management about network connection of module is important for normal service of module base personal robot. Unpredictable network disconnection is influenced to whole robot performance in module base personal robot. For this, Middleware must be offer two important function. The first is function of error detection and reporting about abnormal network disconnection. Therefore, middleware need method for network error detection and module management to consider special quality that each network device has. The second is the function recovering that makes the regular service possible. When the module closed from connection reconnects, as this service reports connection state of the corresponding module, the personal robot resumes the existing service. In this paper proposed method of network connection management for to support fault tolerant about network error of network module based personal robot.