• 한국정밀공학회지
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• 제20권9호
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• pp.205-213
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• 2003

This study describes the mathematical equation of drawdown test model and introduces the experimental test apparatus and procedure to estimate the desorption rate ratio of a filter. The characteristics of a hydraulic filtration system of drawdown test were demonstrated by numerical simulation for various properties of filters and operation conditions. Experiments for three kinds of fuel filters were conducted according to the proposed test method. And the test results of desorption rate ratio were compared with those values anticipated in precedent multipass filtration tests. Experimental results revealed the validation of drawdown test method proposed in this study. Domestic fuel filter yielded high desorption rate ratio comparing with other foreign products, which means that the Beta ratio decreases a lot during the test. The results also showed that filtration system model could be developed including desorption rate ratio to estimate the variable Beta ratio in service life.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.141-144
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• 2003

This paper proposes an analytical model of off-line feed rate scheduling to obtain an optimum feed rate for high speed machining. Off-line feed rate scheduling is presented as an advanced technology to regulate cutting forces through change of feed per tooth, which directly affects variation of uncut chip thickness. In this paper, the feed rate scheduling model was developed using a mechanistic cutting force model using cutting-condition-independent coefficients. First, it was verified that cutting force coefficients are not changed with respect to cutting speed. Thus, the feed rate scheduling model using the cutting-condition-independent coefficients can be applied to set the proper feed rates for high speed machining as well as normal machining. Experimental results show that the developed fred rate scheduling model makes it possible to maintain the cutting force at a desired level during high speed machining.

• 한국정밀공학회지
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• 제16권10호
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• pp.94-100
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• 1999

Micro-EDM is widely used in machining of miro-parts such as micro-shafts and micro-holes. In order to select proper machining conditions and to reduce the machining time, it is necessary to understand machining characteristics under various machining conditions. Micro-hole machining tests were performed with round shape electrodes with different capacitances and voltages of the power source. The effects of the electrode rotational speed and diameter on the machining rate were also observed. From the experimental results, it was found that capacitance and voltage have significant effects on machining rate and the machined surface integrity. With higher capacitance and higher voltage, higher machining rate was observed together with poorer surface integrity. The electrode diameter was also found to have an effect on the machining rate and electrode wear.

• Journal of Biosystems Engineering
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• 제42권2호
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• pp.98-103
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• 2017

Purpose: Precision agriculture includes determining the right amount of nitrogen for a specific location in the field. This work focused on developing and validating a model using variable rate nitrogen application based on the estimated SPAD value from the ground-based image sensor. Methods: A variable rate N application based on the decision making system was performed using a sensor-based variable rate nitrogen application system. To validate the nitrogen application decision making system based on the SPAD values, the developed N recommendation was compared with another conventional N recommendation. Results: Sensor-based variable rate nitrogen application was performed. The nitrogen deficiency level was measured using the image sensor system. Then, a variable rate application was run using the decision model and real-ti me control. Conclusions: These results would be useful for nitrogen management of corn in the field. The developed nitrogen application decision making system worked well, when considering the SPAD value estimation.

• 한국정밀공학회지
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• 제19권1호
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• pp.196-203
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• 2002

Generally, non-uniformity and removal rate are important factors on measurements of both wafer and die scale. In this study, we verify the effects of the pressure and relative velocity on the results of the chemical mechanical polishing and the effect of pattern density on inter layer dielectric chemical mechanical polishing of patterned wafer. We suggest an appropriate modeling equation, transformed from Preston\`s equations which was used in glass polishing, and simulate the removal rate of patterned wafer in chemical mechanical polishing. Results indicate that the pressure and relative velocity are dominant factors for the chemical mechanical polishing and pattern density effects on removal rate of pattern wafers in die scale. The modeling is well agreed to middle and low density structures of the die. Actually, the die used in Fab. was designed to have an appropriate density, therefore the modeling will be suitable for estimating the results of ILD CMP.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 추계학술대회 논문집
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• pp.891-892
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• 2012

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 추계학술대회 논문요약집
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• pp.175-175
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• 2003

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 춘계학술대회 논문집
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• pp.61-62
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• 2008

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 추계학술대회 논문집
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• pp.185-186
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• 2009

• Geomechanics and Engineering
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• 제36권2호
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.