The results of the measurements using an optical surface roughness meter are shown according to the angle changes of 0, 0.5, 1, 1.5, 2, and 3°. Through the experiment, it can be seen that the measurement value is 3.140 at 0°, 3.148 at 0.5°, 3.140 at 1°, 3.151 at 1.5°, 5.078 at 2°, and 4.790 at 3° setting. In addition, the test statistic (P) value is 0.000, which is smaller than the significance level of 0.005, so it was confirmed through the experiment that a measurement error occurs according to the angle change when measuring the surface roughness.

This study focuses on optimizing the uniform pressing process in precision manufacturing, addressing challenges posed by surface roughness and height differences between components. In real-world conditions, such irregularities can lead to non-uniform pressure distribution during pressing, negatively affecting product quality. To mitigate these issues, a buffer protection layer was introduced between the press and components. The optimization process was conducted through finite element analysis (FEA) to determine the ideal material properties, including elastic modulus, Poisson's ratio, and thickness of the buffer layer. Two surface roughness scenarios were examined to assess the impact of surface conditions on pressing uniformity. The results indicate that a higher elastic modulus, Poisson’s ratio, and thicker buffer layers are more effective in achieving uniform pressing, particularly under rougher surface conditions. This study provides a practical solution for improving the precision and reliability of pressing processes, ensuring better product consistency and enhancing overall manufacturing efficiency.

농업에서 거친 토양 표면은 다양한 문제를 일으킨다. 물, 토양, 씨앗, 비료와 같은 자원을 낭비하여 생산비를 높이고 환경에도 부정적인 영향을 끼친다. 또, 농업 기계는 거친 토양에서 균형을 잡기 어려워 농부들의 편의성을 해치고, 장비의 내구성과 자율 주행 성능을 떨어뜨리는 등 정밀농업의 실현을 방해한다. 거친 토양 표면은 입자가 큰 토양으로 구성되어 있을 가능성이 높으며, 이는 식물 생장을 방해하고 물빠짐에도 영향을 준다. 거친 표토를 측정하는 방식은 농지 전체를 측정하기보단 일부 지점의 거칠기를 측정하여 나머지 지점의 거칠기를 추정하는 것이 다수다. 따라서, 본 연구는 무인비행체(UAV)를 이용해 효율적으로 표토 거칠기를 측정할 수 있는 방안을 제안하고자 한다. 실험은 경상남도 밀양시 부북면에서 40m 높이에서 180장, 86%의 중첩률로 획득한 항공 사진을 이용했다. 이미지 데이터를 바탕으로 만들어진 조밀 점군에서 파이썬으로 중심점으로부터 일정한 반경 이내에 있는 가까운 주변 8개 점을 선택하여 고도차를 이용하여 결과값을 계산하였다. TRI 지수, Roughness 지수, 표준편차 세 가지 지표는 계산 후 농지에 시각화되었다. 일부 지점에서 측정한 표토 거칠기를 바탕으로 나머지 농지에 대한 거칠기 값을 추정하는 방식과 달리, 본 연구는 모든 지점에서의 거칠기 지수를 점군 단계에서 습득할 수 있는 방식을 통해 측정의 정밀도를 높이고 농지 운영을 돕고자 하였다.

PURPOSES : The skid resistance between tires and the pavement surface is an important factor that directly affects driving safety and must be considered when evaluating the road performance. In especially wet conditions, the skid resistance of the pavement surface decreases considerably, increasing the risk of accidents. Moreover, poor drainage can lead to hydroplaning. This study aimed to develop a prediction equation for the roughness coefficient—that is, an index of frictional resistance at the interface of the water flow and surface material—to estimate the thickness of the water film in advance to prevent human and material damage. METHODS : The roughness coefficient can be changed depending on the surface material and can be calculated using Manning's theory. Here, the water level (h), which is included in the cross-sectional area and wetted perimeter calculations, can be used to calculate the roughness coefficient by using the water film thickness measurements generated after simulating specific rainfall conditions. In this study, the pavement slope, drainage path length, and mean texture depth for each concrete surface type (non-tined, and tined surfaces with 25-mm and 16-mm spacings) were used as variables. A water film thickness scale was manufactured and used to measure the water film thickness by placing it vertically on top of the pavement surface along the length of the scale protrusion. Based on the measured water film thickness, the roughness coefficient could be back-calculated by applying Manning's formula. A regression analysis was then performed to develop a prediction equation for the roughness coefficient based on the water film thickness data using the water film thickness, mean texture depth, pavement slope, and drainage path length as independent variables. RESULTS : To calculate the roughness coefficient, the results of the water film thickness measurements using rainfall simulations demonstrated that the water film thickness increased as the rainfall intensity increased under N/T, T25, and T16 conditions. Moreover, the water film thickness decreased owing to the linear increase in drainage capacity as the mean texture depth and pavement slope increased, and the shorter the drainage path length, the faster the drainage, resulting in a low water film thickness. Based on the measured water film thickness data, the roughness coefficient was calculated, and it was evident that the roughness coefficient decreased as the rainfall intensity increased. Moreover, the higher the pavement slope and the shorter the drainage path length, the faster the drainage reduced the water film thickness and increased the roughness coefficient (which is an indicator of the friction resistance). It was also evident that as the mean texture depth increased, the drainage capacity increased, which also reduced the roughness coefficient. CONCLUSIONS : As the roughness coefficient of the concrete road surface changes based on the environmental factors, road geometry, and pavement surface characteristics, we developed a prediction equation for the concrete pavement roughness coefficient that considered these factors. To validate the proposed prediction equation, a sensitivity analysis was conducted using the water film thickness prediction equation from previous studies. Existing models have limitations on the impact of the pavement type and rainfall intensity and can be biased toward underestimation; in contrast, the proposed model demonstrated a high correlation between the calculated and measured values. The water film thickness was calculated based on the road design standards in Korea—in the order of normal, caution, and danger scenarios—by using the proposed concrete pavement roughness coefficient prediction model under rainy weather conditions. Specifically, because the normal and caution stages occur before the manifestation of hydroplaning, it should be possible to prevent damage before it leads to the danger stage if it is predicted and managed in advance.

여름철은 타 계절에 비해 장마와 불안정한 대기 등으로 인하여 빗길 교통사고의 위험성이 크게 증대될 수 있으며, 최근 5년 (2018~2022)간 여름철 빗길 교통사고는 전체 빗길 교통사고의 39%를 차지할 정도로 높은 수준이다. 이러한 빗길 운전은 노면의 배수 불량 및 미끄럼 저항 감소 등으로 인하여 수막현상을 발생시키게 된다. 이에 본 연구에서는 우천 시 도로의 안전성 강화 및 사고 위 험을 최소화하기 위한 요소인 수막두께를 산정하기 위하여 Manning의 평균 유속식을 기반으로 콘크리트 노면의 조도계수 예측 모델을 개발하는 것을 목표로 하였다. 조도계수의 영향인자를 고려하기 위하여 실외 강우 모의 장비를 이용하여 콘크리트를 타설한 뒤 실험 인자로 포장 경사, 배수거리, 강우강도, 노면 조직 특성을 고려하였으며, 이 중 노면 조직 특성은 타이닝 처리를 하지 않은 구간만 고 려한 타 연구의 기존 예측 모델 단점을 보완하기 위하여 16, 25mm 간격의 타이닝 표면 처리한 구간을 추가로 고려하였다. 수막두께 측정은 측정 범위 0.3~5mm의 수막두께 측정 게이지를 제작하여 강우가 모사된 조건에서 배수 거리 1~5m 이내 지점의 노면 조직 상 단과 수면이 접하는 수직 높이를 총 3회 측정하여 평균값을 사용하였다. 실측된 수막두께 데이터베이스를 기반으로 Manning 공식을 이용하여 조도계수를 역산한 결과, 강우강도가 증가함에 따라 조도계수는 감소하였으며, 이는 강우의 증가로 인해 물의 흐름과 콘크리 트 노면 사이의 마찰 저항 감소에 기인한 것으로 판단되었다. 또한 포장 경사가 높고 배수 거리가 짧을수록 배수성이 증가하여 마찰 저항의 지표인 조도계수가 증가하는 것으로 확인되었다. 평균 조직 깊이에 따른 조도계수 영향의 경우, 평균 조직 깊이가 증가할수록 콘크리트 표면에 노출되는 표면적이 증가하여 수막두께가 얕게 생성되고, 얕은 수심으로 인해 물의 흐름 저항이 감소하여 조도계수는 감소하는 것으로 산정되었다. 이후 135개의 데이터를 종합하여 조도계수를 종속변수로 하고 강우강도, 포장경사, 배수거리, 평균 조직 깊이, 수막두께를 독립변수로 하는 회귀분석을 수행하여 조도계수 산정식을 개발하였다.

Painting pretreatment is an important task in determining the life of painting as it removes rust or foreign substances from the painting surface and gives adhesion between the painting surface and the painting surface. Since painting pretreatment is an important task, IMO strictly requires that the painting pretreatment surface be maintained at a Sa 2.5 grade and the surface roughness is 30μm~75μm. Painting pre-processing is an important task that determines the lifespan of a painting, but it is done through visual inspection by the inspector, and the quality varies depending on the inspector. In this study, in order to develop a quality measurement system for the painting pretreatment surface, Matlab2023b was used to determine the range of appropriate quality brightness by comparing the brightness of the painting pretreatment surface and surface roughness.

Injection molding is a process of shaping resin materials by heating them to a temperature above their melting point and then using a mold. The resin material is injected into and cooled within the mold cavity, solidifying into the desired shape. The core and cavity components that make up the mold cavity are crucial elements for the precision molding in injection molding. In the case of precision mold production, the application of 5-axis machining technology is required to ensure high machining quality for complex shapes, and among these factors, the tool angle is a critical machining condition that determines the surface roughness of the workpiece. In this study, we aim to measure the surface roughness of the machined surface of KP4A specimens during machining processes with variations in the tool angle and analyze the correlation between the tool angle and surface roughness.

The cutting process, which is a key processing technology in various industrial fields is achieving continuous growth, and the demand for high-quality cutting surfaces is continuously demanded. Plasma cutting continues to be studied for its excellent workability and productivity, but problems with cutting surface quality such as dross formation occur, so research to secure excellent cutting surface quality through appropriate control of process variables is essential. In this study, we propose a method for predicting surface roughness using real-time current and cutting speed data obtained while performing plasma cutting on A106 B steel pipe. Surface roughness was predicted based on the RBF algorithm applicable to prediction and control models. It was shown that the surface roughness of the plasma cutting surface can be predicted with the arc current waveform and process speed data. This study can be used as a basic study to control the surface roughness of the cut surface in real time.

Carbon steel pipes, which are essentially used in the manufacturing industry, are used in various fields due to the advancement of the industry, and a cutting process is essentially applied to pipes manufactured in a nominal size. The cutting process is the most basic and first process used to obtain a material in a desired shape, and it can affect the quality of subsequent processes such as welding or painting, so high-quality cutting surfaces are essential. Therefore, due to the advantage of improving productivity, it is essential to study to secure the appropriate quality of the cutting surface of the plasma cutting process, which is widely used in the industrial field. In this study, the effect of cut surface quality according to process parameters in the plasma cutting process for carbon steel pipe materials was analyzed. The surface roughness was measured to determine the quality of the cut surface, and the relationship between the surface roughness and the process variables was confirmed by selecting the arc current and cutting speed, which are identified as the main factors forming the surface roughness, as process variables.

PURPOSES : For most local governments, including that of Gangwon-do, the establishment of an organized pavement management system is insufficient, resulting in problems such as inefficient distribution and use of maintenance budgets for deteriorated road pavements. In this study, we aimed to contribute to the establishment of a more reasonable road maintenance strategy by developing a model for predicting the annual international roughness index (IRI) change for national highway asphalt pavements in Gangwon-do based on big data analysis. METHODS : Data on independent and dependent variables used for model development were collected. The collected data were subjected to exploratory data analysis (EDA) and data preprocessing. Independent variable candidates were selected to reduce multicollinearity through correlation analysis and specific conditions. A final model was selected, and sensitivity analysis was performed. RESULTS : The final model that predicts annual IRI change uses independent variables such as annual temperature range, minimum temperature, freeze-thaw days, IRI, surface distress (SD), and freezing days. The sensitivity analysis confirmed that the annual IRI change was affected in the order of annual temperature range, minimum temperature, freeze-thaw days, IRI, SD, and freezing days. CONCLUSIONS : Road maintenance can be performed rationally by predicting future pavement conditions using the model developed in this study. The accuracy of the prediction model can be improved if additional data, such as material properties and pavement thickness, are obtained in future studies.

The surface of carbon films deposited with inverted plasma fireballs is analysed in this paper. Measurements were conducted with Raman spectroscopy, atomic force microscopy and nanoindentation. The latter was used to obtain Young’s modulus as well as Martens and Vickers hardness. The roughness of the film was measured by atomic force microscopy and its thickness was measured. It was shown with Raman spectroscopy that the films are homogeneous in terms of atomic composition and layer thickness over an area of about 125 × 125 mm. Furthermore, it was demonstrated that inverted plasma fireballs are a viable tool for obtaining homogeneous, large area carbon films with rapid growth and very little energy consumption. The obtained films show very low roughness.

PURPOSES : The initial smoothness of concrete pavement surfaces must be secured to ensure better driving performance and user comfort. The roughness was measured after hardening the concrete pavement in Korea. When the initial roughness is poor, relatively large-scale repair works, such as milling or reconstruction must be performed. Hence, a method to measure the roughness of the concrete pavements in realtime during construction and immediately correct the abnormal roughness was developed in this study. METHODS : The profile of a concrete pavement section was measured at a construction site using sensors that were attached to the tinning equipment of the paver. The measured data included outliers and noise caused by the sensor and vibration of the paving equipment, respectively, which were further calibrated. Consequently, the calibrated data were input into the ProVAL program to calculate the roughness based on the international roughness index (IRI). Additionally, the profile of the section was re-measured using another method to verify the reliability of the calculated IRI. RESULTS : The profile data measured at the concrete pavement construction site were calibrated using methods, such as overlapped boxplot outlier removal and low-pass filtering. The outlier data from the global positioning system (GPS), which was installed to identify the construction distance, was also calibrated. The IRI was calculated using the ProVAL program by matching the measured profile and GPS data, and applying the moving average method. The calculated IRI was compared to that measured using another method, and the difference was within the tolerance. CONCLUSIONS : A method to measure the roughness of the concrete pavements in real time during construction was developed in this study. Hence, the performance of concrete pavements can be improved by enhancing the roughness of the pavement considerably using the aforementioned method.

Recently, halogen lamps for vehicle exterior lamp systems are being replaced by LEDs (Light Emitting Diode) in consideration of miniaturization, power consumption, life, luminance, and eco-friendliness. Due to regulations on the amount of light required, luminance, light uniformity, and glare prevention, it is required to develop a light guide for controlling a light source of an LED lamp for a vehicle. For the development of the light guides, the development of machining technology that can cut micro patterns of hundreds of micrometers scale into surface roughness of tens of nanometers scale must be preceded. In this study, the effect of variations in cutting conditions on surface roughness was analyzed through experiments. The micro patterns was manufactured by cutting into STAVAX material, and the surface of the micro patterns was super-finished using a ball-shaped PCD (polycrystalline diamond) tool without flutes. In experiments, the cutting conditions of the super-finishing process were varied, and the varied cutting conditions were feed rate, radial depth of cut, and spindle speed

The function of coolant in machining is to reduce the frictional force in the contact area in between the tool and the material, and to increase the precision by cooling the work-piece and the tool, to make the machining surface uniform, and to extend the tool life. However, cutting oil is harmful to the human body because it uses chlorine-based extreme pressure additives to cause environmental pollutants. In this study, the effect of cutting temperature and surface roughness of titanium alloy for medical purpose (Ti-6Al-7Nb) in eco-friendly ADL slot shape machining was investigated using the response surface analysis method. As the design of the experiment, three levels of cutting speed, feed rate, and depth of cut were designed and the experiment was conducted using the central composite planning method. The regression expressions of cutting temperature and surface roughness were respectively obtained as quadratic functions to obtain the minimum value and optimal cutting conditions. The values from this formula and the experimental values were compared. As a result, this study makes and establishes the basis to prevent environmental pollution caused by the use of coolant and to replace it with ADL (Aerosol Dry Lubricant) machining that uses a very small amount of vegetable oil with high pressure.