• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.86-98
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• 2022

Recently, many studies have been conducted to improve quality by applying machine learning models to semiconductor manufacturing process data. However, in the semiconductor manufacturing process, the ratio of good products is much higher than that of defective products, so the problem of data imbalance is serious in terms of machine learning. In addition, since the number of features of data used in machine learning is very large, it is very important to perform machine learning by extracting only important features from among them to increase accuracy and utilization. This study proposes an anomaly detection methodology that can learn excellently despite data imbalance and high-dimensional characteristics of semiconductor process data. The anomaly detection methodology applies the LIME algorithm after applying the SMOTE method and the RFECV method. The proposed methodology analyzes the classification result of the anomaly classification model, detects the cause of the anomaly, and derives a semiconductor process requiring action. The proposed methodology confirmed applicability and feasibility through application of cases.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.168-173
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• 2022

As the function of a product is advanced and the process is refined, the yield in the fine manufacturing process becomes an important variable that determines the cost and quality of the product. Since a fine manufacturing process generally produces a product through many steps, it is difficult to find which process or equipment has a defect, and thus it is practically difficult to ensure a high yield. This paper presents the system architecture of how to build a smart manufacturing system to analyze the big data of the manufacturing plant, and the equipment factor analysis methodology to increase the yield of products in the smart manufacturing system. In order to improve the yield of the product, it is necessary to analyze the defect factor that causes the low yield among the numerous factors of the equipment, and find and manage the equipment factor that affects the defect factor. This study analyzed the key factors of abnormal equipment that affect the yield of products in the manufacturing process using the data mining technique. Eventually, a methodology for finding key factors of abnormal equipment that directly affect the yield of products in smart manufacturing systems is presented. The methodology presented in this study was applied to the actual manufacturing plant to confirm the effect of key factors of important facilities on yield.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.219-225
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• 2009

The primary purpose of this study is to build computer models referring overall flow of complex and various semiconductor wafer manufacturing process and to implement a educational model which operates with a presentation tool showing device design. It is important that Korean semiconductor industries secure high competitive power on efficient manufacturing management and to develop technology continuously. Models representing the FAB processes and the functions of each process are developed for Seoul National University Semiconductor Research Center. However, it is expected that the models are effective as visually educational tools in Korean semiconductor industries. In addition, it is anticipated that these models are useful for semiconductor process courses in academia. Scalability and flexibility allow semiconductor manufacturers to customize the models and perform simulation education. Subsequently, manufacturers save budget.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.298-301
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• 2001

In semiconductor manufacturing, wafer fabrication is the most complicated and important process, which is composed of several hundreds of process steps and several hundreds of machines involved. The productivity of the manufacturing mainly depends on how well they control balance of WIP flow to achieve maximal throughput under short manufacturing cycle time. In this paper mathematical formulation is suggested for the stepper scheduling, in which cycle time reduction and maximal production is achieved.

• International Journal of Quality Innovation
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• v.6 no.3
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• pp.173-189
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• 2005

A life-cycle assessment (LCA) is based on the attention given to the environmental protection and concerning the possible impact while producing, making, and consuming products. It includes all environmental concerns and the potential impact of a product's life cycle from raw material procurement, manufacturing, usage, and disposal (that is, from cradle to grave). This study assesses the environmental impact of the ultra pure water process of semiconductor manufacturing by a life-cycle assessment in order to point out the heavy environmental impact process for industry when attempting a balanced point between production and environmental protection. The main purpose of this research is studying the development and application of this technology by setting the ultra pure water of semiconductor manufacturing as a target. We evaluate the environmental impact of the Precoat filter process and the Cation/Anion (C/A) filter process of an ultra pure water manufacturing process. The difference is filter material used produces different water quality and waste material, and has a significant, different environmental influence. Finally, we calculate the cost by engineering economics so as to analyze deeply the minimized environmental impact and suitable process that can be accepted by industry. The structure of this study is mainly combined with a life-cycle assessment by implementing analysis software, using SimaPro as a tool. We clearly understand the environmental impact of ultra pure water of semiconductor used and provide a promotion alternative to the heavy environmental impact items by calculating the environmental impact during a life cycle. At the same time, we specify the cost of reducing the environmental impact by a life-cycle cost analysis.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.356-363
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• 2013

Mechanical molding press which is used for transformation process during semiconductor manufacturing process has structural deformations by pressure. If these deformations have over limit range, life of the press itself can be reduced and it will be exerted on a bad effect for quality of the semiconductor. In this research, the main plates and links of a press are analyzed in relation to the structural deformations caused by pressure excluding thermal deformations. After modifying the modeling, the analysis is performed again to determine optimal design of the press, and this design is introduced to ensure that most of the stresses on the main plates are within safe allowable limits. As a result, an optimal design method for the structure is investigated to produce the desired pressure even when the size of the main structure is minimized.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.571-580
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• 2008

Little attention has been given to semiconductor manufacturing in the chemical engineering and process systems engineering perspective in spite of the fact that it consists of numerous chemical processes. This paper particularly investigates the issues in semiconductor manufacturing supply chain management. From the personal industrial experience and research progresses, relevant research and information will be introduced to address the key issues and challenges. Some remarks for future research challenges are made in the end.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.153-161
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• 2016

Semiconductor manufacturing has suffered from the complex process behavior of the technology oriented control in the production line. While the technological processes are in charge of the quality and the yield of the product, the operational management is also critical for the productivity of the manufacturing line. The fabrication line in the semiconductor manufacturing is considered as the most complex part because of various kinds of the equipment, re-entrant process routing and various product devices. The efficiency and the productivity of the fabrication line may give a significant impact on the subsequent processes such as the probe line, the assembly line and final test line. In the management of the re-entrant process such as semiconductor fabrication, it is important to keep balanced fabrication line. The Performance measures in the fabrication line are throughput, cycle time, inventory, shortage, etc. In the fabrication, throughput and cycle time are the conflicting performance measures. It is very difficult to achieve two conflicting goal simultaneously in the manufacturing line. The capacity of equipment is important factor in the production planning and scheduling. The production planning consideration of capacity can make the scheduling more realistic. In this paper, an input and scheduling rule are to achieve the balanced operation in semiconductor fabrication line through equipment capacity and workload are proposed and evaluated. New backward projection and scheduling rule consideration of facility capacity are suggested. Scheduling wafers on the appropriate facilities are controlled by available capacity, which are determined by the workload in terms of the meet the production target.

• Analytical Science and Technology
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• v.5 no.4
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• pp.359-366
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• 1992

Using micro-Raman spectrometer, we investigated the evaluation of microstress on silicon surface after the local thermal oxidation. The induced stress of silicon surface after local thermal oxidation shows maximum value at the interface of silicon oxide and active area. The smaller the size of active area, the larger stress. From the evaluation of three other device isolation processes, A, B and moB, whose active size has $0.45{\mu}m$ in length, moB process is turned out to have the lowest stress value and the smallest bird's beak effect.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.144-149
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• 2022

A cryogenic Mixed Refrigerant Joule-Thomson refrigeration cycle was designed to be applied to the semiconductor etching process with non-flammable constituents. 3-stage cascade refrigerator, single mixed refrigerant Joule-Thomson refrigerator, and 2-stage cascade type mixed refrigerant Joule-Thomson refrigerator are analyzed to figure out the coefficient of performance. Non-flammable mixture of argon(Ar), tetrafluoromethane(R14), trifluoromethane (R23) and octafluoropropane(R218) were utilized to analyze the refrigeration cycle efficiency. The designed refrigeration cycle was adapted to cool down the coolant of HFE7200(Ethoxy-nonafluorobutane, C₄F₉OC₂H₅) with certain constraints. Maximum coefficient of performance of the refrigeration system is obtained as 0.289 for the cooling temperature lower than -100℃. The detailed result of the coefficient of performance according to the mixture composition is discussed in this study.