• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.218-225
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• 2009

This paper considers a parallel-machine scheduling problem with job release times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines so as to minimize the weighted sum of setup times, delay times, and tardy times. A mathematical model for optimal solution is derived and a meta heuristic algorithm based on the improved ant colony system is proposed in this paper. The performance of the meta heuristic algorithm is evaluated through compare with optimal solutions using randomly generated several examples.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.1-8
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• 2023

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

• Journal of Power Electronics
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• v.7 no.3
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• pp.181-190
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• 2007

This paper presents a novel circuit topology of a DC bus line series switch and parallel snubbing capacitor-assisted soft-switching PWM full-bridge inverter type DC-DC power converter with a high frequency planar transformer link, which is newly developed for high performance arc welding machines in industry. The proposed DC-DC power converter circuit is based upon a voltage source-fed H type full-bridge soft-switching PWM inverter with a high frequency transformer. This DC-DC power converter has a single power semiconductor switching device in series with an input DC low side rail and loss less snubbing capacitor in parallel with the inverter bridge legs. All the active power switches in the full-bridge arms and DC bus line can achieve ZCS turn-on and ZVS turn-off transition commutation. Consequently, the total switching power losses occurred at turn-off switching transition of these power semiconductor devices; IGBTs can be reduced even in higher switching frequency bands ranging from 20 kHz to 100 kHz. The switching frequency of this DC-DC power converter using IGBT power modules can be realized at 60 kHz. It is proved experimentally by power loss analysis that the more the switching frequency increases, the more the proposed DC-DC power converter can achieve a higher control response performance and size miniaturization. The practical and inherent effectiveness of the new DC-DC converter topology proposed here is actually confirmed for low voltage and large current DC-DC power supplies (32V, 300A) for TIG arc welding applications in industry.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.141-148
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• 2011

Support vector machines have been extensively studied and utilized in pattern recognition area for years. One of interesting applications of this technique is music/speech classification for a standardized codec such as 3GPP2 selectable mode vocoder. In this paper, we propose a novel approach that improves the speech/music classification of support vector machines. While conventional support vector machine optimization techniques apply during training phase, the proposed technique can be adopted in classification phase. In this regard, the proposed approach can be developed and employed in parallel with conventional optimizations, resulting in synergistic boost in classification performance. We first analyze the impact of kernel width parameter on the classifications made by support vector machines. From this analysis, we observe that we can fine-tune outputs of support vector machines with the kernel width parameter. To make the most of this capability, we identify strong correlation among neighboring input frames, and use this correlation information as a guide to adjusting kernel width parameter. According to the experimental results, the proposed algorithm is found to have potential for improving the performance of support vector machines.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.1-10
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• 2011

In this study, we consider a capacity planning problem where the number of machines at each workstation is determined in manufacturing systems of top-edge electronic products such as semiconductor or display. The considered manufacturing system is the typical hybrid flowshop which has identical parallel machines at each workstation and the setup operation occurs when the types of consecutively processed products are different. The objective of the problem is finding good combinations of the numbers of machines at all workstations, under the given capital amount for purchasing machines. Various heuristic methods for determining the numbers of machines at workstations are proposed and the performances were tested through a series of computational experiments. In the study, a simulation model has been developed in order to simulate the considered manufacturing system with dynamic orders and complex process. The simulation model is also used for conducting the computational comparison test among various proposed methods.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.989-998
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• 2013

We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.108-121
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• 2008

Dispatching rule for parallel machines with multi product is proposed in this paper, In current market,customer's request for higher quality is increasing, In accordance with such demand, manufacturers are focusingon improving the quality of the products. Such shift in production objective is risky. The possibility ofneglecting another important factor in customer satisfaction increases, namely due dates. From the aspect ofimproving quality, frequency of product assignment to limited number of high performance machines willincrease. This will lead to increased waiting time which can incur delays, In the case of due date orientedproduct dispatch, Products are assigned to machines without consideration for quality. Overall deterioration ofproduct quality is inevitable, In addition, Poor products will undergo rework process which can increase delays.The objective of this research is dispatching products to minimize due date delays while improving overallquality. Quality index is introduced to provide means of standardizing product quality. The index is used toassure predetermined quality level while minimizing product delays when dispatching products. Qualitystandardization method and dispatching algorithm is presented. And performance evaluation is performed withcomparison to various dispatching methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1679-1685
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• 2015

This paper examines the effect of the magnetization pattern on the partial demagnetization of a permanent magnet (PM) machine that uses a ferrite magnet. Although the use of halbach-magnetized PM (HMPM) arrays in PM machines has been dramatically increasing because of their attractive features, the demagnetization characteristics of HMPM arrays have not yet been examined. In this study, two analyses of the demagnetization characteristics of HMPM arrays and parallel magnetized PMs (PMPMs) are performed, with the demagnetization characteristics being analyzed using a finite element method. According to our results, partial demagnetization occurred dramatically in the HMPM arrays. Thus, it is important to consider the vulnerability of HMPM arrays when designing PM machines.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.9
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• pp.761-769
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• 2008

The majority of mechanical parts are manufactured by milling machines. Hence, geometrically efficient algorithms for tool path generation and physical considerations for better machining productivity with guarantee of machining safety are the most important issues in milling tasks. In this paper, an optimized path generation algorithm for direction parallel milling which is commonly used in the roughing stage is presented. First of all, a geometrically efficient tool path generation algorithm using an intersection points-graph is introduced. Although the direction parallel tool path obtained from geometric information have been successful to make desirable shape, it seldom consider physical process concerns like cutting forces and chatters. In order to cope with these problems, an optimized tool path, which maintains constant MRR in order to achieve constant cutting forces and to avoid chatter vibrations at all time, is introduced and the result is verified. Additional tool path segments are appended to the basic tool path by using a pixel based simulation technique. The algorithm has been implemented for two dimensional contiguous end milling operations, and cutting tests are conducted by measuring spindle current, which reflects machining situations, to verify the significance of the proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.2
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• pp.131-142
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• 1991

The concept of criterion function is proposed as a framework for comparing the geometric and computational characteristics of various nonlinear programming approaches to linear programming such as the method of centers, Karmakar's algorithm and the gravitational method. Also, we discuss various computational issues involved in obtaining an efficient parallel implementation of these methods. Clearly, the most time consuming part in solving a linear programming problem is the direction finding procedure, where we obtain an improving direction. In most cases, finding an improving direction is equivalent to solving a simple optimization problem defined at the current feasible solution. Again, this simple optimization problem can be seen as a least squares problem, and the computational effort in solving the least squares problem is, in fact, same as the effort as in solving a system of linear equations. Hence, getting a solution to a system of linear equations fast is very important in solving a linear programming problem efficiently. For solving system of linear equations on parallel computing machines, an iterative method seems more adequate than direct methods. Therefore, we propose one possible strategy for getting an efficient parallel implementation of an iterative method for solving a system of equations and present the summary of computational experiment performed on transputer based parallel computing board installed on IBM PC.