• Journal of Digital Contents Society
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• v.5 no.4
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• pp.251-256
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• 2004

The flatness of a silicon wafer concerned with ULSI chip is one of the most critical parameters ensuring high yield of wafers. That is necessary to constitute the circuit with high quality for he surface of silicon wafer, which comes to be base to make the direct circuit of the semiconductor, Flatness, therefore, is the most important factor to guarantee it wafer with high quality. The process of polishing is one of the most crucial production line among 10 processing stages to change the rough surface into the flatnees with best quality. Currently at this process, it is general for an engineer in charge to observe, judge and control the model of wafer from the monitor of measuring equipment with his/her own eyes to enhance the degree of flatness. This, however, is quite a troublesome job for someone has to check of process by one's physical experience. The purpose of this study is to approach the model of wafer with digital contents and to apply the result of the research for an algorithm which enables to control the polishing process by means of measuring the degree of flatness automatically, not by person, but by system. In addition, this paper shows that this algorithm proposed for the whole wafer flatness enables to draw an estimated algorithm which is for the thickness of sites to measure the degree of flatness for each site of wafer.

• Journal of Digital Contents Society
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• v.3 no.1
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• pp.113-122
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• 2002

The flatness of a silicon wafer concerned with ULSI chip is one of the most critical parameters ensuring high yield of wafers. The polishing process that measures and controls the flatness of a silicon wafer is one of the important process in various processes for production silicon wafer, which are still being done today by manual. But engineers in polishing process are requested to have many experiences and to check silicon wafers one by one. In this paper, we propose an algorithm used interpolation that estimates wafer's shape and sorts wafers automatically, then we can control the flatness of wafers in polishing process by automatic system.

• Journal of Drive and Control
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• v.17 no.1
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• pp.37-43
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• 2020

An intelligent excavator can be divided into Machine Guidance (MG), semi-automatic, and unmanned by technology. The MG technology excavator is equipped with a tilt sensor on each link of the excavator and a GPS is installed on the excavator body to inform the user of the position of the excavator bucket end. Machine control (MC) technology that assists the user's work can be divided into semi-automatic and fully automatic technology. The semi-automatic MC equipment has already been commercialized by Komatsu and Caterpillar. The MC excavator is equipped with an electro-hydraulic system, sensors and controllers to control the excavator bucket end according to the user's needs. In this study, the semi-automated excavator modified based on manual excavator, is equipped with an electro-hydraulic system, a controller system, multi-sensors and a control algorithm is developed to assist in excavation work such as leveling and grading. By applying the developed technology, it was possible to confirm productivity improvement compared to manual digging and leveling work. In the future, further research to improve the accuracy of the hydraulic precision control and collaborative work with heterogeneous construction equipment such as dump truck and automated collaboration tasks technology could be developed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2337-2342
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• 2008

In this paper, we propose the novel approach to enhance the visual quality of the digital image with adaptively sharpening and removing the noise. Image enhancement is performed in two ways. The pixels in the high dynamics area are sharpened by the adaptive unsharp mask with the parameter, which is derived using the statistical information of the image. On the other hand, the proposed algorithm do not perform the sharpening process in the uniform area that may cause the undesired artifact due to noise amplification, rather it performs smoothing to suppress the noise in this area. The decision, which process will be applied at the pixel, is also controlled by the statistics of the pixel dynamics. The proposed algorithm enhances the visual quality almost automatically by sharpening and smoothing at the same time with less parameter selection.