• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.62-67
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• 2011

Grinding process is executed in the final machining stage to meet the quality requirements. In generally the ground surface of workpiece is affected by dressing condition as well as grinding condition. In order to estimate the roughness of workpiece, the several roughness models have been researched. These models defined the specific parameters and considered the several parameters which affect to roughness as multiply relationship among them. However, the multiply relationship among parameters is not enough to show the complicated grinding mechanism. Therefore, the neural network algorithm is used in this paper to predict the ground roughness for the plunge grinding. The proposed structure is composed of the initial roughness as well as final roughness model. The input parameters of proposed neural network are referred with the existing roughness model's. The performance of the proposed model is verified through experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.5704-5708
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• 2012

In this paper, the algorithm to determine the optimal condition of traverse grinding is proposed by using differential evolution algorithm(DEA). The cost function to determine the optimal grinding condition is designed with considering process cost, production rate, surface roughness. Also, the constraint conditions for grinding such as thermal damage effect, machine tool stiffness, wear parameter of grinding wheel, surface roughness are considered. The algorithm is implemented with LabView software which is widely used at the industrial field. The performance of proposed algorithm is verified by comparing with the result of genetic algorithm(GA) through computer simulation.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.240-246
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• 2000

An in-process estimation of the ground surface roughness is a bottle-neck and an essential field in conventional grinding operation. We defined the dimensionless average roughness factor (D.A.R.F) that exhibits a roughness characteristics of ground surface. The D.A.R.F was composed easily of the absolute average and the standard deviation values which were the analytic parameters of the acoustic emission (AE) signal generated during the machining process. The theoretical equation between the surface roughness and the D.A.R.F has been derived from the linear regressive analysis and verified its availability through the experimentation on the surface grinding machine.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.285-288
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• 2000

This paper deals with the theoretical estimation and its experimental verification of grinding wheel wear in surface grinding process. A theoretical formulation is provided to predict the grinding wheel wear in surface grinding. The associated surface roughness and grinding force are also investigated both theoretically and experimentally. Through a series of simulations and experiments, it is shown that the predictions are in good agreement with the experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.4
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• pp.46-54
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• 1995

This paper presents a simple method for measurenemt of roughness of ground surfaces. The present method utilizes fluxes of scattered lights condensed through lenses aligned along the specular direction. A theoretical analysis is preformed for the purpose of investigating the possibility of the method as well as determining the experimental condition. Experiments are also performed to show the effectiveness and robustness of the proposed method. The theoretical and experimental results show that the proposed method is simple enouth to implement and has a potential to identify a wide range of roughness of ground surfaces.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.429-434
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• 2000

• Journal of the Korean Society for Precision Engineering
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• v.24 no.10
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• pp.13-18
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.260-260
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• 2004

연삭 가공은 대직경 반도체 웨이퍼의 경면 가공, 산업용 정밀 부품, 광학 분야의 고정밀급 렌즈 등 여러 산업 분야의 각종 정밀 부품의 마무리 공정에 적총되어 제품의 질을 좌우하는 필수적인 공정이라 할 수 있다. 이러한 연삭 가공은 높은 치수 정밀도와 양호한 표면 거칠기 및 제품의 형상을 동시에 만족시킬 수 있는 가공 기술로서 , 대직경 웨이퍼 생산에 있어서, 고정밀ㆍ고품위의 웨이퍼를 양산하는데 적합한 기술로 인식되고 있다.(중략)

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.167-173
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• 1999

This paper presents results of monitoring grinding processes with on-the-machine measurement of surface roughness by using nux ratios of scattered lights. A compact, on-the-machine surface roughness sensor. which consists of a diodelaser and several optic units. is developed. The control unit is also developed. The developed sensor together with the controller is applied for monitoring grinding processes of two different grinding machines. Experimental results show that the nux ratios and their standard deviations measured by the developed sensor over the entire ground surface are useful for monitoring grinding conditions. In particular, the sensor and the control unit are proved to be useful for monitoring grinding processes in order to detect abnormal grinding conditions and dressing time.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.27-36
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• 2001

본고에서는 고정도 제품을 생산하는 연삭기에 대해 가공물 및 연삭 공구인 연삭 숫돌을 기상에서 측정하기 위한 여러 가지 방법들을 소개하였고 일부는 적응 예를 기술하였다. 소개된 기상 측정장치들은 특히 반복 공정이 필요한 연삭 현장에서 생산성 향상을 위해 유용하게 활용될 수 있을 것으로 생각된다. 그러나 관련 연구가 지속된다면 연삭기의 작업조건 자동 설정, 연삭 상태 진단 등, 연삭기의 지능화에도 적극적으로 응용될 수 있을 것으로 기대된다.