In automated Tape substrate (TS) inspection, machine vision is widely adopted for their high throughput and cost
advantages. However, conventional methods are overly sensitive to foreign particles or have limitations in detecting
three dimensional defects such as top over-etching. In an attempt to complement vision inspection systems, we proposed
utilizing x-ray inspection. To implement x-ray inspection in TS application, we developed a prototype fast and high
spatial resolution x-ray imaging sensor which functions at frame rate in excess of 30 fps and has a spatial resolution of
20 µm. In this paper, the development of the sensor and its performance is addressed and the efficiency of the x-ray
inspection in detecting top over-etching defects will be shown with experimental studies.
Tape substrate (TS) product is a high-density circuit pattern on thin film substrate, and it requires precise and high resolution imaging system for inspection. We introduce here a TS inspection system developed, where the products are fed through a reel to reel system, and a series of inspection algorithms based on a referential method. In the system, it is so hard to achieve consistent images for such a thin and flexible materials as TS product that the images suffer from individual, local distortion during the image acquisition. Since the distortion results in relatively big discrepancy between an inspection image and the master one, direct image to image comparison approach is not available for inspection. To inspect the pattern in a more robust way in this application, we propose a graph matching method where the patterns are modeled as a collection of lines with link points as features. In the offline teaching process, the graph model is achieved from skeleton of the master image, which is collected as a data base. In the run time, a boundary tracking method is used for extracting the graph model from an inspection image instead of a skeleton process to reduce the computation time. By comparing the corresponding graph models, a line that is linked to undesired endpoints can be detected, which becomes an open or short defect. Through boundary tracking approach, we can also detect boundary defects such as pattern nick and protrusions as well.
Serious pattern defects and particles co-exist on the glass and only a few defects can cause serious quality problem. Now, if there would be a way to classify the defect by its potential lethality, it would be useful to control the product quality and loss of review time. This paper presents a method to classify the defect by using reviewing images. First, several defect types were investigated to develop an algorithm. In next, efficiency of the algorithm was verified in a plant. The result was good enough to utilize the information of classified defect type. Finally, the algorithm was applied to remove the information of trivial defects. The result was good to increase a throughput of whole process under little risk.
Novel all-fiber optic temperature sensors based on hollow optical fibers (HOFs) are presented. The HOFs with an air hole diameter of 8um at the center are fabricated through elaborate controls of MCVD and fiber drawing process. Two types of all-fiber temperature sensors are described. One is an all-fiber temperature sensor composed of a short HOF serially concatenated between a pair of long-period fiber gratings using a B/Ge-codoped core single mode fiber (SMF). The broadband pass-band tuning range of 84.3nm, covering both S and C band, is observed in the range from 25 to 215°C. Transmission peak is linearly shifted showing negative slope of -0.44nm/°C at 1500nm region. Its design, fabrication arts, and device integration are explained with characteristics of output filter spectrum and temperature tuning. The other is an in-line fiber etalon temperature sensor using a short HOF segment fusion-spliced between standard SMFs. This device is characterized in terms of wavelength shift according to temperature for HOFs with and without Ge-doped ring core. Temperature sensitivity of 3.38×10-5/°C and dynamic range of 20dB are observed over the range from 25 to 330°C at 1550nm. It is confirmed that the experimental results for both fiber optical sensors show a good agreement with theoretical analysis.
Small particles are one of the biggest sources that cause loss in semiconductor and flat panel display industry. Therefore, it is important to control them during their manufacturing process. To achieve this goal, exact measurement of particles is first required. Laser light scattering is the most widely used technique for diagnosis of particles because it does not disturb flow field and enables real time and spatially resolved analysis. Measurement of nonspherical aggregates comprised of small primary particles is difficult compared with spherical particles because they have very complex morphology. In addition, most researches on aggregates using light scattering are limited to point measurement, which requires much time to inspect large area and is difficult to observe unsteady phenomenon. Motivated by this, we have developed a laser light scattering method for simultaneous measurement of spatial distributions of aggregate size and morphology.
Silica aggregates that were generated in Methane/air premixed flame were used as test particles. Multiangular planar light scattering measurement was carried out using a sheet beam of Ar ion laser and an intensified charge coupled device (ICCD) camera as a light source and a detector, respectively. The result was interpreted based on the Rayleigh-Debye-Gans scattering theory for fractal aggregates to obtain the mean radius of gyration and fractal dimension that are the parameters characterizing aggregate size and morphology. The suitability of our new technique was confirmed by experiment using conventional light scattering.
LCD(Liquid Crystal Display) became one of the most popular display devices in these days. The TFT(Thin Film Transistor) substrate is the key part of active matrix LCD. TFT is an electrical device to activate a displaying cell. To display an image precisely, several millions of identical transistors are patterned on a wide glass panel. Since a minute damage on the pattern can causes a serious defect to display, it is important to inspect the pattern precisely. Taking the advantage of the fact that the pattern of good cell should be identical to that of adjacent cells, it would be a convenient way to compare a cell with its neighbor cells to find a defect. In practical applications, if the period of repetition could be represented as an integer number of digitized image pixel, it would be possible to find a damaged pixel readily. However, the period of pattern depends on the product size and cannot be determined as an integer always. In this paper, so called, pseudo-matching magnification algorithm has been introduced to solve the problem. A digital image was magnified and period of pattern can be determined as an integer from the processed image. It has been shown that the defects could be enhanced after the preprocessing of digital image. As a result, a TFT-pattern inspection system has been developed and it has been shown the proposed method is compatible for the inspection of repeated pattern.
To detect the electrical fault of a thin film transistor (TFT) panel for the LCD, a polymer-dispersed-liquid-crystal (PDLC) modulator is used to convert the electric field of TFT substrate to an image. The PDLC changes its light transmittance proportional to electric field strength so that electric faults can be detected without physically contacting to the surface. Specific pattern signals are applied to the data and gate electrodes of the panel to charge the pixel electrodes and the image sensor detects the change of transmittance of PDLC that is positioned in proximity distance above the pixel electrodes. The image represents the status of electric field of the TFT panel reflected on the PDLC so that the characteristic of PDLC itself plays an important role to accurately quantify the defects.
In this paper, a sample PDLC modulator is manufactured and compared with the commercially available one. The dynamics of PDLC modulator is analyzed and the image of electric field of the arrayed electrodes on TFT panel is acquired. The signal pattern to the electrodes of TFT panel and modulator should be selected based on the response characteristics of the PDLC for better image quality. The retention time of PDLC is a key factor for the determination of signal pattern.
The fabrication of an electric field detector using electro- optic LiNbO3 (LN) single crystal has been studied for the application to check the electric field of a conductively patterned panel. When this electric field detector moves on the surface of the panel, air gap which is close enough for the given field intensity and resolution has to be maintained constantly not to damage the patterns on the surface For the effective detection of electric field change in this air gap state, LN single crystal was selected because of the relatively high electro-optic coefficient, transmittance and low dielectric constant. X-cut LN and Z- cut LN structures were selected to estimate the applicability of LN single crystal by the simulation on the optical intensity variation and electric field distribution of the various structures. As the air gap was increased from 0 to 40 (μm) in the X-cut LN structure, half-wave voltage (Vπ) was increased from 400 to 700 (V) and optical intensity variation with unit voltage (Q) was decreased from 1.3 to 0.17. At the air gap of 10 μm in the Z-cut LN structure, (Vπ) was about 100-150 (V) and Q was 6.7 (%/V) much larger than that of the X-cut LN structure. Form these characteristics, Z-cut LN structure proved to be applicable for the electric field detector because the optical intensity variation (.08μW) was sufficient in the ac driving voltage region (±20
V) of the real system.
A new voltage sensing method has been tried using a n electro-luminescence effect. Optical images of the electric potential of conductive planar patterns could be obtained by this method. The brightness of the sensor surface is proportional to the voltage that is applied to the pattern electrode and the image is captured. By processing the image, defective part of the pattern electrode can be identified. This method is contact-free so that it can be applied to what is covered by an insulator layer. Also, we propose a driving method of the sensor that enables measuring DC voltages. This method may be applied to what is covered by an insulator layer. Also, we propose a driving method of the sensor that enables measuring DC voltages. This method may be applied to inspect the fine conductive patterns in non-contacting way during the fabrication process of display devices such as thin film transistor liquid crystal display panels.