• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.1032-1035
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• 2000

Increasing demands on precision machining with computerized numerical control (CNC) machines have necessitated that the tool to move not only position error as small as possible, but also with smoothly varying feedrates in space. This paper presents a new high precision interpolation algorithm for 3-dimensional (3D) Non-Uniform Rational B-Spline (NURBS) curve in the reference-pulse CNC technique. Based on the minimum path error strategy, real-time NURBS interpolator was developed in software and this was implemented with a PC-NC milling machine. The several experimental results have shown that the proposed NURBS interpolator is useful for the high precision machining of complex shapes. It is expected that this algorithm can be applied to the CNC machines for the machining of 3D free-form surfaces.

• 한국시뮬레이션학회논문지
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• 제8권1호
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• pp.63-76
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• 1999

Recently in manufacturing environment, manufacturing order is characterized by unstable market demand, shorter product life cycle, a variety of product and shorter production lead time. In order to adapt this manufacturing order, flexible manufacturing systems(FMS) in manufacturing technology advances into the direction that machines become further versatile functionally and that tools are controlled by fast tool delivery device. Unlike conventional FMS to mainly focus on part flow, it is important to control tool flow in single-stage multimachine systems(SSMS), consisting of versatile machines and fast tool delivery device. This research is motivated by the thought that exact estimation of tool competition at part release in SSMS enhances the system performance. In this paper, in SSMS under dynamic tool allocation strategy to share tools among machines, we propose real-time part release and tool allocation algorithms which can apply real factory and which can improve system performance.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1999년도 춘계학술대회 논문집
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• pp.60-64
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• 1999

Recently in manufacturing environment, manufacturing order is characterized by unstable market demand, shorter product life cycle, a variety of product and shorter production lead time. In order to adapt this manufacturing order, flexible manufacturing system(FMS) in manufacturing technology advances into the direction that machines become further versatile functionally and that tools are controlled by fast tool delivery device. Unlike conventional FMS to mainly focus on part flow, it is important to control tool flow in single-stage multimachine systems(SSMS), consisting of versatile machines and fast tool delivery device. In this paper, in SSMS under dynamic tool allocation strategy to share tools among machines, we propose real-time part release and tool allocation algorithms which can apply real factory and which can improve system performance.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.371-375
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• 2004

Fault diagnosis is one of the most studied problems in process engineering. Recently, great research interest has been devoted to approaches that use classification methods to detect faults. This paper presents an application of a newly developed classification method - support vector machines - for fault diagnosis in an industrial case. A real set of operation data of a motor pump was used to train and test the support vector machines. The experiment results show that the support vector machines give higher correct detection rate of faults in comparison to rule-based diagnostics. In addition, the studied method can work with fewer training instances, what is important for online diagnostics.

• Asia pacific journal of information systems
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• 제20권2호
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• pp.23-37
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• 2010

Conventional Support Vector Machines (SVMs) have been utilized as classifiers for binary classification problems. However, certain real world problems, including corporate bond rating, cannot be addressed by binary classifiers because these are multi-class problems. For this reason, numerous studies have attempted to transform the original SVM into a multiclass classifier. These studies, however, have only considered nominal classification problems. Thus, these approaches have been limited by the existence of multiclass classification problems where classes are not nominal but ordinal in real world, such as corporate bond rating and multiclass customer classification. In this study, we adopt a novel multiclass SVM which can address ordinal classification problems using ordinal pairwise partitioning (OPP). The proposed model in our study may use fewer classifiers, but it classifies more accurately because it considers the characteristics of the order of the classes. Although it can be applied to all kinds of ordinal multiclass classification problems, most prior studies have applied it to finance area like bond rating. Thus, this study applies it to a real world customer level classification case for implementing customer relationship management. The result shows that the ordinal multiclass SVM model may also be effective for customer level classification.

• 디지털산업정보학회논문지
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• 제4권2호
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• pp.1-12
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• 2008

Home network is a technology that provides possibilities of monitoring/controling/mutilating-recognition between optional home network machines in residences. Currently, home network or other networks like entertainment, residential electronic networks are jumbled together with heterogeneous networks in a rampaging condition. In a reality of high expectation for home networks system like the mutual application for various machines, we are required to have the unification technology for conveniences to satisfy expectations. This thesis reflects how to develop Java applications or mutual products based on convenient interfaces actually that process various sensors which create real time data stream in Java platform through Java based sensor data-stream processing embedded middleware design and realization in real time.

• 대한조선학회논문집
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• 제42권1호
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• pp.64-72
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• 2005

Digital manufacturing is a technology to simulate the real manufacturing process using the virtual model representing the physical schema and the behavior of the real manufacturing system including resources, processes and product information. Therefore, it can optimize the manufacturing system or prevent the bottleneck processes through the simulation before the manufacturing plan is executed. This study presents a method to apply the digital manufacturing technology for the steel cutting process in shipyard. The system modeling of cutting shop is carried out using the IDEF and UML which is a visual modeling language to document the artifacts of a complex system. Also, virtual NC simulators of the cutting machines are constructed to emulate the real operation of cutting machines and NC codes. The simulators are able to verify the cutting shape and estimate the precise cycle time of the planned NC codes. The validity of the virtual model is checked by comparing the real cutting time and shape with the simulated results. It is expected that the virtual NC simulators can be used for accurate estimation of the cutting time and shape in advance of real cutting work.

• 경영과학
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• 제17권1호
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• pp.41-54
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• 2000

in the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.

• 한국경영과학회지
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• 제22권4호
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• pp.115-131
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• 1997

The problem addressed in this paper is to minimize the deviations of workloads assigned to worker and to maximize the total utilizations(degree of skill) between workers and machines simultaneously. Each worker can handle the set of machines with the different degree of skill and each machine has the workloads needed to be processed. Also, each worker has to be assigned to at least one machine with the minimum workload deviation. This problem can be formulated as a preemptive goal programming with generalized assignment constraints. The proposed algorithm consists of two phases. First, a capacitated circulation network is constructed to assign the workers to machines with the maximum total utilizations while considering workloads balance. Then, a refinement process is applied to the split machines to satisfy the feasibility condition. The real industrial application in a plastic extrusion manufacturer is included along with several computational experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권4호
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• pp.301-308
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• 2009

In the modern life, machines are used for various areas in industries as the advance of science and industrial development has proceeded. In many machines, the rotating machines play an important role in many processes. Therefore, the development of fault diagnosis and monitoring system for rotating machines is required. An ubiquitous sensor network (USN) is a combination of the key computer science and engineering area technology including the wireless network, embedded system hardware and software, communication, real-time system, etc. It collects environmental information to realize a variety of functions. In this work, a data reduction algorithm for USN based remote fault diagnostic system which can be easily applied to previously built factories is proposed. To verify the feasibility of the proposed scheme, some simulations and experiments are executed.