• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1812-1816
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• 2011

This research developed chemical flow control system(CFCS) essential for spinner equipment in nano semiconductor manufacturing process under the 100nm to prevent complex process defect due to missing spread after chemical injection. The devices developed in this research, which can be swiftly replaced in case abnormal state element changes or wafer manufacturing defect occurs, are anticipated to improve module yield as well as real-time monitoring on the state element. In addition, as a result of mounting H/W and S/W system to control detailed operation sequence in production line and executing performance check and verification, we can be exactly detected in five abnomal process type.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4467-4471
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• 2013

In this research, developed full-scan photoresist coating system(FPCS) can improve the efficiency of the photoresist coating system essential for spinner equipment in nano semiconductor manufacturing process. The devices developed in this research, which can be swiftly replaced in case abnormal state element changes or wafer manufacturing defect occurs, are anticipated to improve module yield as well as real-time monitoring on the state element in order to prevent the complex process defect due to the photoresist miss coating.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.74-84
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• 2022

As the semiconductor industry develops, the difficulty of newly required process technology becomes difficult, and the importance of production yield and product reliability increases. As an effort to minimize yield loss in the manufacturing process, interests in the process defect process for facility diagnosis and defect identification are continuously increasing. This research observed the plasma condition changes in the multi oxide/nitride layer deposition (MOLD) process, which is one of the 3D-NAND manufacturing processes through optical emission spectroscopy (OES) and monitored the result of whether the change in plasma characteristics generated in repeated deposition of oxide film and nitride film could directly affect the film. Based on these results, it was confirmed that if a change over a certain period occurs, a change in the plasma characteristics was detected. The change may affect the quality of oxide film, such as the film thickness as well as the interfacial surface roughness when the oxide and nitride thin film deposited by plasma enhenced chemical vapor deposition (PECVD) method.

• Proceedings of the Materials Research Society of Korea Conference
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• 1994.11a
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• pp.63-63
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• 1994

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.63-64
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• 2007

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.43-48
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• 2017

Semiconductors are leading the development of industrial technology, leading to miniaturization and weight reduction of electronic products as a leading technology, we are dragging the electronic industry market Especially, the semiconductor manufacturing process is composed of highly accurate and complicated processes, and effective production is required Recently, a vision system combining a computer and a camera is utilized for defect detection In addition, the demand for a system for measuring the shape of a fine pattern processed by a special process is rapidly increasing. In this paper, we propose a vision algorithm using mask image to detect scratch defect of semiconductor pockage. When applied to the manufacturing process of semiconductor packages via the proposed system, it is expected that production management can be facilitated, and efficiency of production will be enhanced by failure judgment of high-speed packages.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.120-126
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• 2009

There are many different types of surface defects on semiconductor Integrated Chips (IC's) caused by various factors during manufacturing process, such as cracks, foreign materials, chip-outs, chips, and voids. These defects must be detected and classified by an inspection system for productivity improvement and effective process control. Among defects, in particular, foreign materials and chips are the most difficult ones to classify accurately. A vision system composed of a carefully designed optical system and a processing algorithm is proposed to detect and classify the defects on QFN(Quad Flat No-leads) packages. The processing algorithm uses features derived from the defect's position and brightness value in the Maximum Likelihood classifier and the optical system is designed to effectively extract the features used in the classifier. In experiments we confirm that this method gives more effective result in classifying foreign materials and chips.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.76-82
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• 1997

The discrimination of flaw shape and sizing is very important subject in the material evaluation for semiconductor and new materials. The aim of this paper is to investigate the spectrum analysis of artificial defect signal captured from steel ball embedded in the resin. The results show that it can be evaluated quantitatively the size of artificial defect, from the amplitude variation of same frequency if the probe with same diameter and focal length is used. Comparing with the amplitude variation of the high frequency component and low frequency component obtained from the distance of defect center position, it can be estimated steel ball and flat bottm defect.

• Applied Science and Convergence Technology
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• v.25 no.5
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• pp.85-87
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• 2016

Coincidence Doppler broadening and positron lifetime methods in positron annihilation spectroscopy has been used to analyze defect structures in metal, semiconductor and polycrystal, respectively. The S parameter and the lifetime (${\tau}$) value show that the defects were strongly related with vacancies. A positive relationship existed between the scanning electron microscope (SEM) images and the positron annihilation spectroscopy (PAS). According to the SEM images and PAS results, measurements of the defects with PAS indicate that it was more affected by the defect than the purity.