• Journal of the Korea Safety Management & Science
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• v.3 no.4
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• pp.103-112
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• 2001

In Factory, as the number of machine is increased the more maintenance efforts are necessary. Multi maintenance issues may occur at a certain time and the determination of maintenance sequence is needed. In this study, we first compare the priority of machines and the impact value using modified FMEA(Failure Mode Effect and Analysis) method. Also, CBR(Case-based Reasoning) approach is applied to retrieve similar fault cases of current machine problem. The proposed methodology will be useful to implement decision support system of maintenance sequence for CMMS/EAM (Computerized Maintenance Management System/Enterprise Asset Management).

• Journal of Korean Society for Quality Management
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• v.17 no.1
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• pp.69-81
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• 1989

This study is concerned with a job sequencing method using the concept of sampling technique in the case of Job Shop. This is the follow study of Kang and Ro (1988) which examined the possibility of application of sampling technique to determine the Job Sequence in the case of Flow Shop. Not only it is very difficult, but also it takes too much time to develop the appropriate job schedules that satisfy the complex work conditions. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions or assumptions. The application areas of these algorithms are also very narrow, so it is very hard to find the appropriate algorithm which satisfy the complex work conditions. In this case it is very desirable to develop a simple job sequencing method which can select the optimal job sequence or near optimal job sequence with a little effort. This study is to examine the effect of sampling job sequencing which can select the good job of 0.01%~5% upper good group. The result shows that there is the sets of 0.05%~23% job sequence group which has the same amount of performance measure with the optimal job sequence in the case of experiment of N/M/G/$F_{max}$. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with consuming a small amount of time. The results of ANOVA show that the only one factor, number of machines is the significant factor for determining the job sequence at ${\alpha}=0.01$. It takes about 10 minutes to compare the number of 10,000 samples of job sequence by personal computer and it is proved that the selection rate of the same job sequence with optimal job sequence is 23.0%, 3.9% and 0.065% in the case of 2 machines, 3 machines and 4 machines, respectively. The area of application can readily be extended to the other work condition.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.29-36
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• 2013

This paper considers common due-date assignment and scheduling on parallel machines. The main decisions are: (a) deter-mining the common due-date; (b) allocating jobs to machines; and (c) sequencing the jobs assigned to each machine. The objective is to minimize the sum of the penalties associated with common due-date assignment, earliness and tardiness. As an extension of the existing studies on the problem, we consider sequence-dependent setup times that depend on the type of job just completed and on the job to be processed. The sequence-dependent setups, commonly found in various manufacturing systems, make the problem much more complicated. To represent the problem more clearly, a mixed integer programming model is suggested, and due to the complexity of the problem, two heuristics, one with individual sequence-dependent setup times and the other with aggregated sequence-dependent setup times, are suggested after analyzing the characteristics of the problem. Computational experiments were done on a number of test instances and the results are reported.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.15-27
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• 1998

In the parallel processing systems, a compiler partitions a loaded program into tasks, allocates the tasks on multiple processors and schedules the tasks on each allocated processor. In this paper we suggest a Genetic Algorithm(GA) based scheduling method to find an optimal allocation and sequence of tasks on each Processor. The suggested method uses a chromosome which consists of task sequence and binary string that represent the number and order of tasks on each processor respectively. Two correction algorithms are used to maintain precedency constraints of the tasks in the chromosome. This scheduling method determines the optimal number of processors within limited numbers, and then finds the optimal schedule for each processor. A result from computational experiment of the suggested method is given.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.71-85
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• 2001

This paper considers a cost model for a U-shaped manufacturing cell formation which incorporates a required number of machines and various material flows together under multi-part multi-cell environment. The model is required to satisfy both the specified operation sequence of each part and the total part demand volume, which are considered to derive material handling cost in U-shaped flow line cells. In the model several cost-incurring factors including set-up for batch change-over, processing time for operations of each part, and machine failures are also considered in association with processing load and capacity of each cell. Moreover, a heuristic for a good machine layout in each cell is newly proposed based on the material handling cost of each alternative sequence layout. These all are put together to present an efficient heuristic for the U-shaped independent-cell formation problem, numerical problems are solved to illustrate the algorithm.

• International Journal of Contents
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• v.12 no.1
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• pp.1-5
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• 2016

To manipulate large video contents, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-wise user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm that extracts key frames using color histograms and matches the video sequences using edge features. To effectively match video sequences with a low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with real sequence show that the proposed video sequence matching algorithm using edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.2
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• pp.93-103
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• 2009

In this paper, we propose a USIM-based Authentication Scheme for 3GPP Network Access. The proposed scheme improves the problems of existing authentication protocol in 3GPP Network such as sequence number synchronization problem, the storage overhead of authentication data, and bandwidth consumption between Serving Network and Home Network. Our proposal is based on the USIM-based Authentication and Key Agreement Protocol that is defined in 3GPP Specification. In our scheme, mobile nodes share a SK with Serving Network and use a time stamp when mobile nodes are performing an authentication procedure with Serving Network. By using time stamp, there is no reason for using sequence number to match the authentication vector between mobile nodes and networks. So, synchronization problem can be solved in our scheme. As well as our scheme uses an authentication vector, the storage overhead of authentication data in Serving Network and bandwidth consumption between networks can be improved.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.121-141
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• 1989

This paper is concerned with a development and evaluation of heuristics for the multi-stage sequence dependent flowshop sequencing. Eighteen heuristics, CAM1, CAM2, and etc., are proposed. The performance measure is a makespan which is to be minimized. The experiment for each algorithm is designed for a 4*3*3 factorial design with 360 observations. The experimental factors are PS(ratio of processing times to setup times), M(number of machines), N(number of jobs). The makespan of the proposed heuristics is compared with the optimal makespan obtained by the complete enumeration of schedules. This yardstick of comparison is called a relative error. The mean relative errors of the eighteen heuristics are from 2.048% to 8.717%. The computational results are analysed using SPSS. The experimental results show that the three factors are statistically significant at 5% level. The simulation for the large size problems is conducted to show having the similar computational results like the small size problems.

• Korean Management Science Review
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• v.11 no.1
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• pp.23-37
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• 1994

This paper discusses the methodology for the operational performance of unit-load automated guided vehicles(AGVs) in a flow-shop-type flexible machining and assembly systems (FM/AS). Throughout the paper, AGVs are working as a carrier and mobile workstation. For a double-loop FM/AS, in which one loop is dedicated to machining and the other to assembly, three AGV operating strategies are proposed. Considering the entering interval and travel time of AGVs between workcenters, the strategies are developed to determine the best job sequence which minimizes the makespan and vehicle idle time. Entering times of AGVs and the required minimum number of AGVs are obtained on the basis of the best job sequence. When the number of AGVs are limited, entering times of AGVs are adjusted to maximize the utilization of AGVs.

• Journal of Korean Society for Quality Management
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• v.17 no.1
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• pp.35-47
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• 1989

This paper is concerned with a development and evaluation of heuristic algorithms for the n-job, M-stage flowshop with sequence dependent setup times. Three heuristic algorithms, CAIDAN, DANNEN and PETROV, are proposed. The makespan is taken as a performance measure for the algorithms. The experiment for each algorithm is designed for a $4{\times}3{\times}3$ factorial design with 360 observations. The experimental factors are PS (ratio of processing times to setup times), M (number of machines), and N (number of jobs). The makespan of the proposed heuristic algorithms is compared with the optimal makespan obtained by the complete enumeration method. The result of comparision of performance measure is called a relative error. The mean relative errors of CAIDAN, DANNEN and PETROV algorithms are 4.488%. 6.712% and 7.282%, respectively. The computational results are analysed using SPSS. The experimental results show that the three factors are statistically signiticant at 5% level.