• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.47-57
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• 2000

In this study, PC-based dicing machine and driving software were constructed for the purpose of automation of wafer cutting process. To automate the machine, hard automation including vision, loading, and software were considered in the development. Auto loading device and vision system were adopted for the increase of productivity, GUI software programmed for the expedient operation. The dicing machine is operated by the control algorithm and some parameters. It is verified that this kind of PC based automation has a great potential compared with the conventional dicing machine when applied to manufacturing some kinds of wafers as a test purpose.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.105-114
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• 2003

In this study, a dicing machine with vision system was built and an algorithm for automatic alignment was developed for dual camera system. The system had a macro and a micro inspection tool. The algorithm was formulated from geometric relations. When a wafer was put on the cutting stage within certain range, it was inspected by vision system and compared with a standard pattern. The difference between the patterns was analyzed and evaluated. Then, the stage was moved by x, y, $\theta$ axes to compensate these differences. The amount of compensation was calculated from the result of the vision inspection through the automatic alignment algorithm. The stage was moved to the compensated position and was inspected by vision for checking its result again. Accuracy and validity of the algorithm was discussed from these data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.3
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• pp.66-71
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• 2016

Reducing the wafer breakage rate and sawing thinner wafers will decrease the cost of solar cells. This study was carried out in order to identify ways to achieve this goal. In this study, the cutting force characteristics using an ingot tilting-type diamond multi wire-sawing machine were analyzed. The cutting force was analyzed while varying the tilting angles and wire speed. The obtained data were analyzed by classifying the tangential cutting force and the normal cutting force. In this cutting force experiment, the difference between the forces was confirmed; it was found that it rises with increasing the tilting angles and decreases when the wire speed elevates. The resulting value can be utilized as basic data for the determination of an ideal cutting recipe.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.1
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• pp.26-33
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• 2016

In this study, a new method to develop a fixed diamond wire for silicon wafer machining by the multi-wire cutting method was developed. The new twist diamond wire has improved performance with high breaking strength and chip flutes structure. According to these characteristics, the new twist diamond wire can be used in the higher speed multi-wire cutting process with a long lifetime. Except the design of the new structure, the twist diamond wire is coating by electroless-electroplating process. It is good for reducing breakage and the falling-off of diamond grains. Based on the silicon material removal mechanism and performance of the wire-cutting machine, the optimal processing condition of the new twist diamond wire has been derived via mathematical analysis. At last, through the tensile testing and the machining experiments, the performance of the twist diamond wire has been obtained to achieve the development goals and exceed the single diamond wire.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.55-61
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• 2009

This paper describes a point of production(POP) system which collects and manages real-time shop floor machining information in a wafer dicing process. The system are composed of POP terminal, line controller and network. In the configuration of the system, LAN and RS485 network are used for connection with the upper management system and down stratum respectively. As a bridge between POP terminal and server, a line controller is used. The real-time information which is the base of production management are collected from information resources such as machine, product and worker. The collected information are used for the calculation of optimal cutting condition. The collection of the information includes cutting speed, spout of pure water, accumulated count of cut in process for blade and wafer defect. In order to manage machining information in wafer dicing process, production planning information is delivered to the shop floor, and production result information is collected from the shop floor, delivered to the server and used for managing production plan. From the result of the system application, production progress status, work and non-working hour analysis for each machine, and wafer defect analysis are available, and they are used for quality and productivity improvements in wafer dicing process. A case study is implemented to evaluate the performance of the system.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.184-189
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• 2005

An experimental study of the femtosecond laser machining of Si materials was carried out. Direct laser machining of the materials for the feature size of a few micron scale has the advantage of low cost and simple process comparing to the semiconductor process, E-beam lithography, ECM and other machining process. Further, the femtosecond laser is the better tool to machine the micro parts due to its characteristics of minimizing the heat affected zone(HAZ). As a result of line cutting of Si, the optimal condition had the region of the effective energy of 2mJ/mm-2.5mJ/mm with the power of 0.5mW-1.5mW. The polarization effects of the incident beam existed in the machining qualities, therefore the sample motion should be perpendicular to the projection of the electric vector. We also observed the periodic ripple patterns which come out in condition of the pulse overlap with the threshold energy. Finally, we could machined the groove with the linewidth of below $2{\mu}m$ for the application of MEMS device repairing, scribing and arbitrary patterning.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1014-1020
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• 2003

We have developed the ultrasonic polishing system to get super finishing that consist of machine part that can rotate and travel the main shaft with power 1.5kW, ultrasonic generator with frequency 20kHz. By using this system we were investigated the characteristics of ultrasonic polishing and deduced the major facters which affect the surface roughness by the experimental plans for three different materials such as ceramic, glass, and wafer, and so could be obtained following results. We could be obtained the excellent surface for hard-to-difficult cutting materials. The rotating speed could be found to be major factor influencing the surface roughness. In the case of ceramic and wafer, we were able to obtain good surface roughness when the feed rate and ultrasonic output is higher. In the case of glass, the surface roughness becames worse when ultrasonic output is higher because of increasing of load affacting on the particles in slurry.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.407-419
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• 2022

The semiconductor fabrication process is complex and time-consuming. There are sometimes errors in the process, which results in defective die on the wafer bin map (WBM). We can detect the faulty WBM by finding some patterns caused by dies. When one manually seeks the failure on WBM, it takes a long time due to the enormous number of WBMs. We suggest a two-step approach to discover the probable pattern on the WBMs in this paper. The first step is to separate the normal WBMs from the defective WBMs. We adapt a hierarchical clustering for de-noising, which nicely performs this work by wisely tuning the number of minimum points and the cutting height. Once declared as a faulty WBM, then it moves to the next step. In the second step, we classify the patterns among the defective WBMs. For this purpose, we extract features from the WBM. Then machine learning algorithm classifies the pattern. We use a real WBM data set (WM-811K) released by Taiwan semiconductor manufacturing company.

• Resources Recycling
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• v.31 no.6
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• pp.60-65
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• 2022

This study presents the carburization process for recycling sludge, which was formed during silicon wafer machining. The sludge used in the carburization process is a mixture of silicon and silicon carbide (SiC) with iron as an impurity, which originates from the machine. Additionally, the sludge contains cutting oil, a fluid with high viscosity. Therefore, the sludge was dried before carburization to remove organic matter. The dried sludge was washed by acid cleaning to remove the iron impurity and subsequently carburized by heat treatment under vacuum to form the SiC powder. The ratio of silicon to SiC in the sludge was varied depending on the sources and thus carbon content was adjusted by the ratio. With increasing SiC content, the carbon content required for SiC formation increased. It was demonstrated that substoichiometric SiC_x (x<1) was easily formed when the carbon content was insufficient. Therefore, excess carbon is required to obtain a pure SiC phase. Moreover, size reduction by high-energy milling had a beneficial effect on the suppression of SiC_x, forming the pure SiC phase.