• 자원환경지질
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• 제27권1호
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• pp.81-91
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• 1994

There has been considerable research dealing with the influence of surface roughness along surfaces of rock discontinuities in relation to the peak shear strength of rock masses. Concepts accepted recently for measuring such strength include estimation of a roughness coefficient such as developed by Barton's studies. The method for estimation the Joint Roughness Coefficient (JRC) value of a measured roughness profile is subjective. The aim of this research is to estimate the JRC value of the roughness of a surface profile in a rock mass system using an objective method. The study of roughness of surfaces has included measurement of fractal geometric characteristics. Once the irregularity of the surface has been described by the fractal dimension, the spatial variation of the surface irregularities can be described using variogram and drift analysis. An empirical relationships between the roughness profiles of selected JRC ranges and their fractal dimension with variogram and drift were derived. The application of analyses of fractal dimension, variogram and drift was novel for the analysis of roughness profiles. Also, an empirical equation was applied to experimental data.

• 한국정밀공학회지
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• 제19권4호
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• pp.73-78
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• 2002

This paper presents a neural network approach to estimate the surface roughness by considering the relationship between the polishing operation parameters and the surface roughness. The neural network model predicts the post-machining surface roughness by using several factors such as pre-machining surface roughness, pressure, feed rate, spindle speed, and the number of polishing as inputs. In this paper, the several neural network models are implemented to estimate the surface roughness by using actual experimental data. The experimental results show that the neural network approach is more appropriate to represent the polishing characteristics of mold and die compared with the results obtained by the approach using exponential function.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.464-468
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• 1996

To evaluate the surface integrity of machined products such as die, the surface roughness measurement is being much used. Especially, for machining automation and promotion of productivity, the surface roughness measurement technique changes from sepatate measuring system after machining process to the on-the-machine measurement. This study is on the surface roughness measurement by using scattered lights for on-the-machine measurement. This system is designed with a simple optical construction. And experiments are implemented with standard roughness specimen to obtain the parameters which are specularly reflected region parameter and diffusely reflected region parameter. To determine the surface roughness quickly, neural network is used. And this system gives the possibility to apply to the various production processes.

• 한국기계가공학회지
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• 제21권5호
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• pp.61-66
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• 2022

This study investigated the characteristics and relationship between surface roughness and vibration according to the cutting conditions in the slot milling of AL7075-T6. The spindle speed, feed, and depth of cut were selected as independent variables and the amplitude of acceleration and surface roughness as dependent variables. Feed affected the surface roughness. As the spindle speed increased, the amplitude of vibration increased in the direction perpendicular to the feed direction. In addition, the amplitude of vibration and surface roughness showed a negative correlation. Under a given feed, the surface roughness improved as the vibration increased.

• 한국표면공학회지
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• 제43권3호
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• pp.159-164
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• 2010

Surface roughness of deposited or etched film strongly depends on ion bombardment. Relationships between ion bombardment variables and surface roughness are too complicated to model analytically. To overcome this, an empirical neural network model was constructed and applied to a deposition process of silicon nitride (SiN) films. The films were deposited by using a pulsed plasma enhanced chemical vapor deposition system in $SiH_4$-$NH_4$ plasma. Radio frequency source power and duty ratio were varied in the range of 200-800 W and 40-100%. A total of 20 experiments were conducted. A non-invasive ion energy analyzer was used to collect ion energy distribution. The diagnostic variables examined include high (or) low ion energy and high (or low) ion energy flux. Mean surface roughness was measured by using atomic force microscopy. A neural network model relating the diagnostic variables to the surface roughness was constructed and its prediction performance was optimized by using a genetic algorithm. The optimized model yielded an improved performance of about 58% over statistical regression model. The model revealed very interesting features useful for optimization of surface roughness. This includes a reduction in surface roughness either by an increase in ion energy flux at lower ion energy or by an increase in higher ion energy at lower ion energy flux.

• 한국기계가공학회지
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• 제1권1호
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• pp.133-140
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• 2002

The object of this paper is to predict the surface roughness using the experiment equation of surface roughness, which is developed with a full factorial design in turning. $3^3$ full factorial design has been used to study main and interaction effects of main cutting parameters such as cutting speed, feed rate, and depth of cut, on surface roughness. For prediction of surface roughness, the arithmetic average (Ra) is used, and stepwise regression has been used to check the significance of all effects of cutting parameters. Using the result of these, the experimental equation of surface roughness, which consists of significant effects of cutting parameters, has been developed. The coefficient of determination of this equation is 0.9908. And the prediction ability of this equation was verified by additional experiments. The result of that, the coefficient of determination is 0.9718.

• 한국기계가공학회지
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• 제18권7호
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• pp.77-82
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• 2019

In this study, we study the change of surface roughness during cutting machining by changing the cutting conditions such as feed rate and spindle velocity with chromium molybdenum steel (SCM415) material and TiCN and TiAlN coated end mill tools. The surface roughness value of the test specimen for SCM415, was found to be 3,000 rpm in TiCN coated end mill and $0.634{\mu}m$ in surface roughness at a feed rate of 100 mm/min. In the TiAlN coated end mill, 300 mm/min, the surface roughness was the best at $0.699{\mu}m$. The overall average surface roughness of each coating tool was better than that of TiAlN.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 추계학술대회 논문집
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• pp.248-253
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• 1997

The ideal surface roughness is obtained by tool geometry and feed rate in face milling. however actual surface roughness is affected by various factors such as cutting conditions. vibration and used tool. To improve the quality and productivity of the machining parts, lots of research on the evaluation of tool life and control of surface roughness has been required. Therefore, the width of flank wear, cutting force, and surface roughness are monitored to analyse the characteristics of surface roughness. This experimental investigation is mainly focused on the characteristics of surface roughness in multi-insert milling using TiN coated tool.

• 한국환경과학회지
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• 제6권6호
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• pp.689-696
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• 1997

This paper discussed effect of the surface roughness and the hydrophobicity of support material on the microbial attachment In a rotating biological contactor. The by- drophoblclty of each support material was determined by the measurement of contact angle of water and the surface roughness was measured by the surface roughness In- strument. Microorganisms have well attached on the surface of more hydrophilic support material like Nylon6 than that of the hydrophobic support material like PE. When the relatively hydrophilic surface was roughen, the microbial attachment was increased but when the relatively hydrophobic surface was roughen, the attachment was slightly In- creased because the hydrophobicity of support material was Increased by roughening the hydrophobic surface. Although both variables, the surface hydrophobicity and the surface roughness, have Influenced the microbial attachment, the influence of the surface roughness overruled that of the surface hydrophobicity. Support material whose surfaces were roughened about 1mm, 6mm and 11mm were allowed for attached 3, 7 and 24hr, but the differences of maximum and minimum attachment of each material gave nearly constant values and similar trend with time.

• 대한공업교육학회지
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• 제34권2호
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• pp.346-362
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• 2009

본 연구는 광섬유센서를 이용하여 표면조도의 간이 비접촉 측정기를 개발하는데 목적이 있다. 광섬유 센서의 장점은 우수한 고속 응답성, 자기의 무영향, 제작의 편이성이다. 광섬유센서 표면조도 측정 원리는 측정물의 표면조도에 따라 반사되는 광의 세기와 기지의 표면조도 값을 일대일 대응시키는 것이다. 반사광의 세기는 센서 프로브로부터 표면까지의 거리와 표면조도에 따른 반사한계각에 따라 결정되는데 본 연구에서는 표면까지의 거리를 일정하게 하여 표면조도에 따른 반사한계각만을 가지고 표면조도가 결정되도록 측정 프로브를 제작하였다. 측정 시스템은 발광부, 수광부과 신호처리부로 구성되었다. 이 실험에서 사용된 표준 측정 재료는 SM45C, STS303과 Al60이었다. 연구결과 첫째, 재료에 따른 표면조도와 센서출력의 상관관계로부터 근사표면조도식을 도출하고 임의 가공된 시료의 표면조도 측정을 통해 근사표면조도식이 유효함을 입증하였다. 둘째, 실제 제작한 간이 광섬유센서 표면조도 측정기가 유용함을 입증하였다.