• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.100-107
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• 2015

Recently as the manufacturers want competitiveness in dynamically changing environment, they are trying a lot of efforts to be efficient with their production systems, which may be achieved by diminishing unplanned operation stops. The operation stops and maintenance cost are known to be significantly decreased by adopting proper maintenance strategy. Therefore, the manufacturers were more getting interested in scheduling of exact maintenance scheduling to keep smooth operation and prevent unexpected stops. In this paper, we proposedan integrated maintenance approach in injection molding manufacturing line. It consists of predictive and preventive maintenance approach. The predictive maintenance uses the statistical process control technique with the real-time data and the preventive maintenance is based on the checking period of machine components or equipment. For the predictive maintenance approach, firstly, we identified components or equipment that are required maintenance, and then machine parameters that are related with the identified components or equipment. Second, we performed regression analysis to select the machine parameters that affect the quality of the manufactured products and are significant to the quality of the products. By this analysis, we can exclude the insignificant parameters from monitoring parameters and focus on the significant parameters. Third, we developed the statistical prediction models for the selected machine parameters. Current models include regression, exponential smoothing and so on. We used these models to decide abnormal patternand to schedule maintenance. Finally, for other components or equipment which is not covered by predictive approach, we adoptedpreventive maintenance approach. To show feasibility we developed an integrated maintenance support system in LabView Watchdog Agent and SQL Server environment and validated our proposed methodology with experimental data.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1103-1110
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• 2022

The old machine tools that have been used for a long time cause both increase in defective rate and decrease in productivity compared to new machines due to wear and failure of their components. In order to improve productivity and quality of machined components through remanufacturing, it is necessary to analyze the wear and failure of major components of old machine tools. In this study, the process for reverse engineering is designed for the remanufacture of planner millers, which belong to a very large machine tool. Also, the suitability of the designed process is verified through the analysis of the selected remanufactured components. In the first step of the process, some major components of the aging planner miller are scanned using a 3D laser scanner. In the next step, reverse engineering is performed using the data obtained through 3D scanning. Finally, wear and failure analysis is performed by comparing the reverse engineering data with the scan data. As a result, this reverse design and wear analysis can complement the insufficient design database and reduce costs in the maintenance of remanufactured products.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.6
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• pp.110-116
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• 2005

A single-piece-machined-part has superior characteristics to an assembly of several pieces of part especially for aircraft components. It is necessary to develop high efficient 'multi-head router machine' for machining a large size single-piece-part on a large scale. In this type machine, many cutting chips are generated. These chips should be removed automatically f3r productivity and part precision. In this study, the design evaluation of the cutting chip collecting apparatus for 'multi-head router machine' was complemented using performance test and finite element analysis.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.1
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• pp.12-17
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• 2013

Fault currents are expressed as a combination of harmonic components and exponentially decaying DC offset components, during the occurrence of fault in power system. The DC offset components are included, when the voltage phase angle of fault inception is closer to $0^{\circ}$ or $180^{\circ}$. The digital protection relay should be detected quickly and accurately during the faults, despite of the distortions of relaying signal by these components. It is very important to implement the robust protection algorithm, that is not affected by DC offset and harmonic components, because most relaying algorithms extract the fundamental frequency component from distorted relaying signal. So, In order to high performance in relaying, advanced DC offset removal filter is required. In this paper, a new DC offset removal filter, which is no need to preset a time constant of power system and accurately estimate the DC offset components with one cycle of data, is proposed, and compared with the other filter. In order to verify performance of the filter, we used collecting the current signals after synchronous machine modeling by ATPDraw5.7p4 software. The results of simulation, the proposed DC offset removal filter do not need any prior information, the phase delay and gain error were not occurred.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.211-217
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• 2007

A nano-imprinting stage has been widely used in various fields of nanotechnology. In this study, an analysis method of a nano-imprinting stage machine using FEM and flexible multi-body kinematics and dynamics has been presented. We have developed a virtual imprinting machine to evaluate the prototype design in the early design stage. The simulation using CAE for the imprinting machine is not only to analyze static and dynamic characteristics of the machine but also to determine design parameters of the components for the imprinting machine, such as dimensions and specifications of actuators and sensors. Structural components as the upper plate, the rotator, the shaft and the translator have been modeled with finite elements to analyze flexibility effects during the precision stage motion. In this paper flexible multi-body dynamic simulation is executed to support robust design of the precision stage mechanism. In addition, we made the 4-axis stage model to compare the dynamic behavior with that of 3-axis stage model.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1841-1851
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• 2018

For the safe and stable operation of the power system, accurate wind power prediction is of great significance. A wind power prediction method based on empirical mode decomposition and improved extreme learning machine is proposed in this paper. Firstly, wind power time series is decomposed into several components with different frequency by empirical mode decomposition, which can reduce the non-stationary of time series. The components after decomposing remove the long correlation and promote the different local characteristics of original wind power time series. Secondly, an improved extreme learning machine prediction model is introduced to overcome the sample data updating disadvantages of standard extreme learning machine. Different improved extreme learning machine prediction model of each component is established. Finally, the prediction value of each component is superimposed to obtain the final result. Compared with other prediction models, the simulation results demonstrate that the proposed prediction method has better prediction accuracy for wind power.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.307-309
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• 1996

This paper analyses a deterministic scheduling problem concerned with manufacturing two types of components at a pre-assembly stage which consists of two independent feeding machines each producing its own type of component. Each type represents a unique component which may have variations in its size or quality. Therefore, the completion time of each component depends on both its type and quality (size) variations. Such manufactured components are subsequently assembled into various component dependent products. The problem has the objective measure of minimizing the total weighted completion time of a finite number of jobs(products) where the completion time of each job is measured by the latest completion time of its two components at the pre-assembly stage. The problem is shown to be NP-complete in the strong sense. A WSPT rule coupled with a machine-aggregation idea is developed for good heuristics which show the error bound of 2.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.514-518
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• 1990

This paper describes an experimental Knowledge-Based Control System, named KBCS, for manufacturing and assembly. The KBCS of five parts and function : data-base, knowledge acquisition, optimization, and graphic monitoring. The KBCS is utilized for a FMS which is of five machine centers and automatic assembly lines. Each machine can perform almost all manufacturing functions which some difference in efficiency. Buffers store temporarily the incoming components and the outing components. Parts arrive at assembly lines after many steps of manufacturing, and the transfer path and time are determined by procedural knowledge of control systems. Nine different incoming components are set up. The total control system is expected to perform four algorithms, timing algorithm ,sequencing algorithm, penalty algorithm, and cart algorithm. The construction of controller require basic components of manufacturing systems in which knowledges are formulated on the base of the results and the repeated simulation of KBCS with graphic monitoring system. Simulation results by KBCS are compared with those by the other rules of manufacturing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.485-486
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• 2006

• Proceedings of the KWS Conference
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• 2007.11a
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• pp.257-259
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• 2007

For this study, SM45C steel rods using generally for power transmission shafts and machine components was selected and welded by Butt-GMAW method. and then it was studied about estimation of fatigue strength and the region of infinite life. From this result, it is demanded that the stress for safety design of machine components using SM45C butt-welded steel rods must be selected in the region of the lowest infinite life of heat affected zone.