• Journal of the Korean Society for Precision Engineering
• /
• v.20 no.2
• /
• pp.146-153
• /
• 2003

Ultrasonic inspection of defects has been focused on the existence of defect in structural material and need has much time and expenses in inspecting all the coordinates (x, y) on material surface. Neural networks can have an application to coordinates (x, y) of defects by multi-point inspection method. Ultrasonic inspection modeling is optimized by neural networks Neural networks has trained training example of absolute and relative coordinate of defects, and defect pattern. This method can predict coordinates (x, y) of defects within engineering estimated mean error $\psi$.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.10
• /
• pp.112-118
• /
• 2021

In this study, an inspection method using a color image is proposed to conduct a real-time inspection of covalent organic framework (COF) films to detect defects, if any. The COF film consists of an upper pattern SR and a lower PI. The proposed system detects the defects of more than 20 ㎛ on the SR surface owing to the characteristics of the pattern, whereas on the PI surface, it detects defects of more than 4 ㎛ by utilizing a micro-optical system. In the existing system, it is difficult for the operator to conduct a full inspection through a high-performance microscope. The proposed inspection algorithm performs the inspection by separating each color component using the color contrast of the pattern on the SR side, and on the PI surface it inspects the bonding state of the mounted chip. As a result, it is possible to confirm the exact location of the defects through the SR and PI surface inspections in the implemented inspection.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.3
• /
• pp.605-610
• /
• 2008

Through welding fabrication, user can feel unsatisfaction of surface quality because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup is an urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualitative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

• Proceedings of the KIEE Conference
• /
• 1988.07a
• /
• pp.959-962
• /
• 1988

This paper describes an automatic visual inspection system for fabric defects based on pattern recognition techniques. The inspection for fabric defects can be separated into three sequences of operations which are the detection of fabric defects[1], the classification of figures of fabric defects, and the classification of fabric defects. Comparing projections of defect-detected images with the predefined complex, the classification accuracy of figures of fabric defects was found to be 95.3 percent. Employing the Bayes classifier using cluster shade in SGLDM and variance in decorrelation method as features, the classification accuracy of regional figure defects was found to be 82.4 percent. Finally, some experimental results for line and dispersed figures of fabric defects are included.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.13 no.2
• /
• pp.11-19
• /
• 1993

It is very essential to get the accurate classification of defects in primary pressure vessel weld for the safety of nuclear power plant. The signal analysis using the digital signal processing and pattern recognition is performed to classify UT defects extracting feature vector from ultrasonic signals. The minimum distance classifier and the maximum likelihood classifier based on statistics were applied in this experiment to discriminate ultrasonics data obtained form both the training specimens (slit, hole) and the testing specimens(crack, slag). The classification rate was measured using pattern classifier. Results of this study show the promise in solving the many flaw classification problems that exist today.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2004.11a
• /
• pp.140-143
• /
• 2004

Chemical mechanical polishing(CMP) is essential technology to secure the depth of focus through the global planarization of wafer. But a variety of defects such as contamination, scratch, dishing, erosion and corrosion are occurred during CMP. Especially, dishing and erosion defects increase the resistance because they decrease the interconnect section area, and ultimately reduce the life time of the semiconductor. Due to this dishing and erosion must be prohibited. The pattern density and size in chip have a significant influence on dishing and erosion occurred over-polishing. Decreasing of abrasive concentration results in advanced pattern selectivity which can lead the uniform removal in chip and decrease of over-polishing. The fixed abrasive pad was applied and tested to reduce dishing and erosion in this paper. Consequently, reduced dishing and erosion was observed in CMP of tungsten pattern wafer with proposed fixed abrasive pad and chemicals.

• Journal of the Korean Society for Precision Engineering
• /
• v.22 no.2
• /
• pp.38-45
• /
• 2005

Chemical mechanical polishing(CMP) has been widely accepted for the planarization of multi-layer structures in semiconductor fabrication. But a variety of defects such as abrasive contamination, scratch, dishing, erosion and corrosion are occurred during CMP. Especially, dishing and erosion defects increase the metal resistance because they decrease the interconnect section area, and ultimately reduce the lift time of the semiconductor. Due to this reason dishing and erosion must be prohibited. The pattern density and size in chip have a significant influence on dishing and erosion occurred by over-polishing. The fixed abrasive pad(FAP) was applied and tested to reduce dishing and erosion in this paper. The abrasive concentration decrease of FAP results in advanced pattern selectivity which can lead the uniform removal in chip and declining over-polishing. Consequently, reduced dishing and erosion was observed in CMP of tungsten pattern wafer with proposed FAP and chemicals.

• The KIPS Transactions:PartB
• /
• v.13B no.4 s.107
• /
• pp.377-382
• /
• 2006

In this paper, two methods based on the use of morphology and pattern matching prior to detect classified defects automatically on the back light unit which is a part of display equipments are proposed. One is the template check method which detects small size defects by using closing and opening method, and the other is the block matching method which detects big size defects by comparing with four regions of uniform blocks. The TC algorithm also can detect defects on the non-uniform pattern of BLU by using revised Otsu method. The proposed method has been implemented on the automatic defect detection system we developed and has been tested image data of BLU captured by the system.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.6 no.1
• /
• pp.11-18
• /
• 1996

Grown-in defects like OISF and FPD in the large diameter(> 8 inch)of silicon crystal are characterized. It was revealed that the presence of the ring-patterned OISF would deterorate the minority life time of the silicon crystal. Through the cooling experiment from the $1250^{\circ}C$, the nucleation of the OISF was confirmed to follow the homogeneous nucleation and growth process. In addition to OISF nucleus, crystal originated particle, which was known to be closely related with FPD (Flow Pattern Defects), was found to depend on the pulling rate of the crystal. Combination of the lower rate of the pulling and the faster cooling near the $950^{\circ}C$ is proposed to be effective method in reducing the generation of these grown-in defects.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.9
• /
• pp.913-917
• /
• 2010

To inspect the defects of printed markings on the surface of IC package, the OCV (Optical Character Verification) method based on NCC (Normalized Correlation Coefficient) pattern matching is widely used. In order to detect the micro pattern defects appearing on the small portion of the markings, a Partitioned NCC pattern matching method was proposed to overcome the limitation of the NCC pattern matching. In this method, the reference pattern is first partitioned into several blocks and the NCC values are computed and are combined in these small partitioned blocks, rather than just using the NCC value for the whole reference pattern. In this paper, we proposed a method to decide the proper number of partition blocks and a method to inspect and combine the NCC values of each partitioned block to identify the defective markings.