• Journal of the Korean Society for Precision Engineering
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• v.24 no.3 s.192
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• pp.108-116
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• 2007

To overcome many defects such as the high product cost, large energy consumption, and big space capacity in conventional mechanical machining, the miniaturization of machine tool and micro factory systems has been envisioned recently. The object of this paper is to research the effect of dynamic characteristic parameters in bolted-joint beams, which is widely applied to the joining of mechanical structures in order to identify structural system characteristics and to predict dynamic behavior according to scale-down from macro to micro system as the development of micro/meso-scale machine tool and micro factories. Modal parameters such as the natural frequency, damping ratio, and mode shape from modal testing and dynamic characteristics from finite element analysis are extracted with all 12 test beam models by materials, by size, and by joining condition, and then the results obtained by both methods are compared.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.619-620
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• 2006

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.340-344
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• 2004

This paper is the performance evaluation of reverse engineering system using simple mechanism. The existing equipment didn't use in the field popularly as it is too expensive. So we constructed the reverse engineering system of simple mechanism using the laser sensor, LM guide, micro step driver and control program. And we caught the Characteristics to measure some product. Finally we confirmed the precision to compare measured data and CAD date.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.162-167
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• 2005

Recently, the advanced industries using micro parts are rapidly growing. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro to micro parts. Also, the method of micro-grooving using micro endmilling is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This study deals with condition monitoring using acoustic emission(AE) signal in the micro-grooving. First, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by using the fuzzy C-means algorithm, which is one of the methods to recognize data patterns. These result is effective monitoring method of micro endmill state by the AE sensing techniques which can be expected to be applicable to micro machining processes in the future.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.193-200
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• 2007

Micro forming is a suited technology to manufacture very small metallic parts(several $mm{\sim}{\mu}m$). Al5083 superplastic alloy with very small grains has a great advantage in achieving micro deformation under low stress due to its relatively low strength at a specific high temperature range. Micro forming of $Zr_{62}Cu_{17}Ni_{13}Al_8$ bulk Metallic glass(BMG) as a candidate material for this developing process are feasible at a relatively low stress in the supercooled liquid state without any crystallization during hot deformation. In this study, the micro formability of Al5083 superplastic alloy and bulk metallic glass, $Zr_{62}Cu_{17}Ni_{13}Al_8$, was investigated with the specially designed micro vibration forming system using pyramid-shape, V-shape and U-shape micro die pattern. With these dies, micro vibration forming was conducted by varying the applied load, time. Micro formability was estimated by comparing the hight of formed shape using non-contact surface profiler system. The vibration load effect to metal flow in the micro die and improve the micro formability of Al5083 superplastic alloy and $Zr_{62}Cu_{17}Ni_{13}Al_8$ bulk Metallic glass(BMG).

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.189-197
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• 2014

Diffractive optical elements (DOEs) - in general a complex pattern of micro- and nano-scale structures - can modulate and transform light in a predetermined way. Their importance is being increased nowadays because they can be designed to handle a number of simultaneous tasks. In view point of machining DOEs, it is a big challenge to fabricate micro- and nano-scale structures on a free-form surfaces. In this paper, the state-of-the-art of the ultra-precision machine tools is reviewed. Also some technical issues which determine the machine tool accuracy are discussed.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.21-31
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• 2023

In this paper, we focused on the problem of evaluating multi-class classification accuracy and simulation of multiple classifier performance metrics. Multi-class classifiers for sentiment analysis involved many challenges, whereas previous research narrowed to the binary classification model since it provides higher accuracy when dealing with text data. Thus, we take inspiration from the non-linear Support Vector Machine to modify the algorithm by embedding dynamic hyperplanes representing multiple class labels. Then we analyzed the performance of multi-class classifiers using macro-accuracy, micro-accuracy and several other metrics to justify the significance of our algorithm enhancement. Furthermore, we hybridized Enhanced Convolution Neural Network (ECNN) with Dynamic Support Vector Machine (DSVM) to demonstrate the effectiveness and efficiency of the classifier towards multi-class text data. We performed experiments on three hybrid classifiers, which are ECNN with Binary SVM (ECNN-BSVM), and ECNN with linear Multi-Class SVM (ECNN-MCSVM) and our proposed algorithm (ECNNDSVM). Comparative experiments of hybrid algorithms yielded 85.12 % for single metric accuracy; 86.95 % for multiple metrics on average. As for our modified algorithm of the ECNN-DSVM classifier, we reached 98.29 % micro-accuracy results with an f-score value of 98 % at most. For the future direction of this research, we are aiming for hyperplane optimization analysis.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.945-950
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• 2004

Surface texturing of tribological application is another attractive technology of friction reducing. Also, reduction of friction is therefore considered to be a necessary requirement for improved efficiency of machine. In this paper attempts to investigate the effect of density for micro-scale dimple pattern on bearing steel flat mated with pin-on-disk. We demonstrated the lubrication mechanism for a Stribeck curve, which has a relationship between the friction coefficient and a dimensionless parameter for lubrication condition. It is found that friction coefficient is depended on the density of surface pattern. It was thus verified that micro-scale dimple could affect the friction reduction.Lubrication condition regime has an influence on the friction coefficient induced the density of micro dimple.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.48-52
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• 2004

Ultrasonic machining is effective for machining of extreme hard and brittle materials, including glass, ceramic, carbide, graphite. The major machining principle involves the direct hammering as well as the impact of abrasive panicles on the workpiece. Also, it involve cavitation erosion. The general workpiece is flat side. This study attempted micro hole machining of a curved surface of glass tube. Ultrasonic machining is fault of the slow machining speed. An experiment does and got 16 seconds validity machining time as increasing the processing speed. Moreover, entrance crack and surface roughness was similar both machining speed is slow and fast. Several micro hole of glass tube machined using one micro tool, but tool wear is infinitesimal.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.166-171
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• 2004

In this study, shape optimization of micro-static mixer with a cantilever beam was accomplished for mixing the mixing efficiency by using successive response surface approximations. Variables were chosen as the length of cantilever beam and the angle between horizontal and the cantilever beam. Sequential approximate optimization method was used to deal with both highly nonlinear and non-smooth characteristics of flow field in a micro-static mixer. Shape optimization problem of a micro-static mixer can be divided into a series of simple subproblems. Approximation to solve the subproblems was performed by response surface approximation, which does not require the sensitivity analysis. To verify the reliability of approximated objective function and the accuracy of it, ANOVA analysis and variables selection method were implemented, respectively. It was verified that successive response surface approximation worked very well and the mixing efficiency was improved very much comparing with the initial shape of a micro-static mixer.