• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.4
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• pp.56-61
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• 2000

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skilful engineers. Grinding operations include a large number of functional parameters, since there are several ways of coping with grinding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workship, the other is the quantitative method which utilizes the experimental data obtained by a sensor. But, they are all difficult to accomplish from the grinding trouble-shooting system. The reason is that grinding troubles are now easily controlled in the quantitative method, and therefore, trouble-shooting has mainly relied on the knowledge of skilful engineers. Thus, there is an important issue of how a grinding trouble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper, basic strategy to develop the grinding database of rule-based model, which is strongly depended upon experience and intuition , is described.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.106-112
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• 2000

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skiful engineers. grinding operations include a large number of functional parameters since there are several ways of coping with ginding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workshop the other is the quantitative method which utilizes the experimental data obtained by sensor. But they are all difficult to accomplish from the grinding trouble-shooting system The reason is that grinding troubles are not accomplish from the grinding trouble-shooting system,. The rason is that grinding troubles are not easily controlled in the quantitative method and therefore trouble-shooting has mainly relied on the knoledge of skiful engineers. Thus there is an important issue of how a grinding touble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper basic strategy to develop the grinding database by taking rule-based model which is strongly depended upon experience and intuition is described.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.492-497
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• 1999

Cognition and control of grinding trouble occurring during the grinding process are classified into a quantitative knowledge which depends on experimental data and qualitative knowledge which relies on skillful engineers. Grinding operations include a large number of functional parameters, since there are several ways of coping with grinding trouble. One is the qualitative method which depends on empirical knowledge utilizing the skilful experts from the workshop, the other is the quantitative method which utilizes the experimental data obtained by sensor. But, they are all difficult to accomplish from the grinding trouble-shooting system. The reason is that grinding troubles are not easily controlled in the quantitative method, and therefore, trouble-shooting has mainly relied on the knowledge of skilful engineers. Thus, there is an important issue of how a grinding trouble-shooting system can be designed and what knowledge is utilized among the large amount of grinding trouble information. In this paper, basic strategy to develop the grinding database of rule-based rule, which is strongly depended upon experience and intuition, is described.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.113-117
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• 1995

Grinding operations is accomplished by rotating a gfinding wheel with lots of random abrasive at high speed, and its object is generally obtained the fanal workpiece surface of high quality as well as the maximization of workpiece removal rate. But, especiallysince grinding operations is related with a large amount of functional parameter, it is actually difficult to therapy that the grinding trouble occurs during the grinding process. Therefore, we trytodesign grinding trouble-shooting system utilizing the back-propagation model of neural network. The conceptual method is produced byidentifying the four parameters derived from the grinding power, and we are design te to the grinding trouble-shooting system on the basis of their data. In this paper, cognition and therapy method tothe grinding trouble which utilizes neural network based four identified models are suggested, and implementation results of computer simulation with respect to the grinding burn and chatter vibration is presented.

• 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 Power System Engineering
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• v.4 no.2
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• pp.25-30
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• 2000

The grinding process is very complex and relates many parameters to control the process. As this reason, a theoretical analysis and a quantitative estimation of the grinding process has not been well established. In this study, the in-process monitoring system was suggested by applying the neural network for monitoring and shooting the malfunction of cylindrical plunge grinding process. This system used the power signals from the electric power meter. This neural network was composed of processing elements [4-(5-5)-3] with 4 identified power parameters. Because sensitivity is blunted some minute vibration components, the simulation result of this system has appeared about 10% erroneous recognition in the uncertain pattern and the average success rate of the trouble recognition was about 90%. Consequently, the developed system, which applied to the power signals, can be recognize enough to monitor the grinding process as in-process.

• Journal of Ocean Engineering and Technology
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• v.13 no.2 s.32
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• pp.11-17
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• 1999

The objective of this paper is to introduce very fast but still stable solution using finite element procedures, and it has been used in an iterative mode for product design applications. A lot of numerical techniques have been developed to deal with the material, geometric and boundary condition non-linearities occurred in the stamping process. One of them, the One-Step FEM is very efficient and useful tool for a design and trouble-shooting in various stamping processes. In this method, the mathod, the material is assumed to deform directly from the initial flat blank to the final configuration without any intermediate steps. The formulation is based on the deformation theory of plasticity and the upper bound theorem. As a result of the calculations, the initial blank shape is obtained, together with the material flow, strains and thickness distribution in the part.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06b
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• pp.191-195
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• 2006

Multivariate data analysis tools were used to improve the understanding of the wet end chemistry and white water system of the Papermill at NorskeCanada Crofton Division. Specifically, the analysis was aimed at identifying what variables were contributing to increased retention aid use and wet end instability. Several models were developed using data sets with up to 88 process variables and over 3000 observations. It was found that increased retention aid use was driven primarily by PCC and TMP usage as well as the addition of Alaskan White Spruce to the TMP furnish.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.48-57
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• 1995

연삭가공중에 발생하는 트러블의 인식과 처리는 공학적 원리에 입각한 방법과 현장 숙련기술자의 경험적 지식을 바탕으로한 방법이있다. 그러나, 연삭가공은 관계되는 가공변수가 많아, 이들 상호간의 관계를 정량적으로 규명할 수 없어 대부분이 숙련자의 지식에 의존하는 것이 현실정이다. 본 논문은 이와같은 점에 착안하여 원통연삭을 대상으로 현장숙련자가 갖고 있는 경험적이고도 정성적인 지식의 호과적인 활용을 위해 계층분석으로 도입하여 이들이 갖고 있는 노하우를 정량화하고, 아울러 공학적원리를 가미한 연삭가공을 트러블 진단. 처리 시스템을 구축하였다. 또한 시스템 구성에 신뢰성을 높이기 위해 폴트 진단 모델을 도입하였다.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.162-169
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• 1998

Lacking for the skilled grinding operator possessed of the experiential knowledges in machine shop, there is the just requirement which includes the establishment of the optimal grinding conditions. Accordingly, we attemt to develope the selection system of optimal grinding conditions such as workpiece velocity, depth of cut and wheel velocity and to add the trouble shooting system by means of the neural network. Those systems are robust to the each machine error and environmental unstable state. In addition. we produce the loaming process that is progressed with additional data modified by skilled operators, and excluding is advanced to similarity of input data.