• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1499-1504
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• 2007

This dissertation explains the construction of the expert system which can manage diagnosis and administration of trouble using circuit diagram through connection between BOM and ability term and makes up for problem which have designed RIMS with name of parts. Also this dissertation explains that existing BOM has no regard organic relation of parts and functional and systematic appearance of the flow of electricity or air. Construction of expert system and "Be enlivened BOM" with flowing electricity and air can solve problems about overlapping parts carrying out other functions with the same name of parts following to simple and physical BOM　management and having mistaken trouble of the end caused by basis for trouble of the end.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.268-274
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• 2009

Human beings can represent state of mind such as psychological state, personality or emotional trouble by the pictures painted on one's own initiative. But in general, it is hard to understand a consulter's unconscious state through one's objective and intentional descriptions only. So one's psychological state and emotional trouble can be understood and cured by color and location information of objects drawn in one's picture. By this reason, a consultant can help and settle a consulter's growth stages of life and emotional trouble through treatment by pictures. In this paper, we proposed a method to find out state of sensitivity by analysis of color and location information represented in a picture and fuzzy inference rules. We applied the proposed method to the states of sensitivity from color information proposed by Alschuler and Hattwick and the psychological states from location information proposed by Grunwald. In the experimental results by the two applications, we verified the proposed sensitivity analysis method is efficient.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.131-137
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• 1994

Detection of grinding trouble occuring during the grinding process is classified into two types, i.e, based on the quantitative and qualitative knowledge. But, since the grinding operation is especially related with a large amount of functional parameters, it is actually defficult to cope with the grinding troubles occuring during process. Therefore, grinding trouble-shooting has difficulty in satisfying the requirement from the user. To cope with the grinding troubles occuring during the process, the application of neural network is on effective way. In this study, we identify the four parameters derived from the AE(Acoustic Emission) signals and present the grinding trouble-shooting system utilizing a back-propagation model of the neural network.

• Journal of the Semiconductor & Display Technology
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• v.19 no.1
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• pp.1-5
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• 2020

In this paper, a predictive maintenance of the robot trouble using the machine learning method, so called MT(Mahalanobis Taguchi), was studied. Especially, 'MD(Mahalanobis Distance)' was used to compare the robot arm motion difference between before the maintenance(bearing change) and after the maintenance. 6-axies vibration sensor was used to detect the vibration sensing during the motion of the robot arm. The results of the comparison, MD value of the arm motions of the after the maintenance(bearing change) was much lower and stable compared to MD value of the arm motions of the before the maintenance. MD value well distinguished the fine difference of the arm vibration of the robot. The superior performance of the MT method applied to the prediction of the robot trouble was verified by this experiments.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.575-578
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• 2003

Recently, because GIS equipment has problems on confidence according to long-time usage, development of diagnosis technique has been importantly recognized. Therefore. measurement and analysis of PD has been generally used much equipment of GIS. But, in case of measurement of PD at field, real trouble signals are difficult to classify noise. Accordingly, a variety of trouble conditions for DS were simulated, and detected signals were analyzed by the application of electrical and mechanical methods. For this analysis, detected signals were accumulated according to phase-magnitude with the application of Induction sensor, and then we analyzed the characteristics. For the simulation experiment, we made DS for 170kV GIS and analyzed the characteristics of detected singals with the application of neural network algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.157-164
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• 2004

Trouble prevention of facilities in operation process plays an important role for improving facilities productivity as production systemization is installed with development of facilities automatization. Condition monitoring predicts machine's internal changes by periodically recording vibration occurred in the machine. This article considers a method of establishing statistical criteria for facilities troubles by utilizing machine condition evaluation and operation limit standards of ISO 10816-3.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.11
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• pp.57-63
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• 1996

Monitoring of grinding troble occurring during the process is classified into the quantitative data which depends upon a sensor and the qualitative knowledge which relies upon an empirical knowledge. Since grinding operation is highly related with a large amount of functional parameters, it is actually deficulty in copying wiht the grinding troubles through the process. To cope with grinding trouble, it is an effective monitoring systems when occurring the grinding process. The use of neural networks is an effective method of detection and/or monitroing on the grinding trouble. In this paper, four parameters which are derived from the AE(Acoustic Emission) signatures are identified, and grinding monitoring system utilized a back propagation learning algorithm of PDP neural networks is presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.78-82
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• 2001

Electronic Weighting Machine is used an electronic scale which has many trouble because of broken load cells. In this paper, we propose an intelligent Diagnosis System will for an electronic weighting machine using fuzzy logic. It's purpose be detect of the load cell's trouble. The electronic circuit of system, which call 'junction box', will be connected resistances in a series at circuit of Wheatstone Bridge for monitoring the condition of load cells.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.358-364
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• 2004

The standardization of the urban transit maintenance system consists of BOM System, maintenance parts code system, and accident/trouble code system standardization. This paper is described only the result of BOM System, maintenance parts code system, and accident/trouble code system standardization. The results of standardization are using urban transit maintenance IT system and apply Expert System, RAMS System, and DATABASE contents of various kinds.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1983.10a
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• pp.118-123
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• 1983

A minicomputer system with the purpose of automations the operations of a Repair Service Bureau is described. SLMOS automates three major functional areas-administration, testing, and report senerations In the administration of repair sevice SLMOS performs a database maintenance functions alons with trouble collection and tracking. Trough ALT, automated testing of customer lines is performed, and the results of the test are utilized to dertermine the action taken to effect a repair. Certain problem areas may be detected and corrected by using the reports senerated by Trouble Report statics and Analysis System.