• Title/Summary/Keyword: Semiconductor Processing

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Optimal Central Control of OHT(Overhead Hoist Transport) in Semiconductor Processing (반도체 공정에 이용되는 지능형 천장 반송 시스템의 최적 중앙제어)

  • Oh Jin-Seok;Kim Hak-Sun
    • Journal of Advanced Marine Engineering and Technology
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    • v.28 no.7
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    • pp.1159-1164
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    • 2004
  • There is an Overhead Hoist Transport(OHT) for delivering the wafer in semiconductor processing. The transfer system is consists of carrier vehicle. rail, and support. OHTCMS(OHT Control and Management System) has to take the feature, such as the optimal control and integration with several OHT. In this paper, ESRA(Efficiency of Shortest - Route Algorithms) is proposed which can be transported optimal route and be prevented collision using the Floyd-Warshall algorithms. The proposed algorithm is verified through consecutive simulation for a long time.

Fabrication of 8 inch Polyimide-type Electrostatic Chuck (폴리이미드형 8인치 정전기척의 제조)

  • 조남인;박순규;설용태
    • Journal of the Semiconductor & Display Technology
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    • v.1 no.1
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    • pp.9-13
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    • 2002
  • A polyimide-type electrostatic chuck (ESC) was fabricated for the application of holding 8-inch silicon wafers in the oxide etching equipment. For the fabrication of the unipolar ESC, core technologies such as coating of polyimide films and anodizing treatment of aluminum surface were developed. The polyimide films were prepared on top of thin coated copper substrates for the good electrical contacts, and the helium gas cooling technique was used for the temperature uniformity of the silicon wafers. The ESC was essentially working with an unipolar operation, which was easier to fabricate and operate compared to a bipolar operation. The chucking force of the ESC has been measured to be about 580 gf when the applied voltage was 1.5 kV, which was considered to be enough force to hold wafers during the dry etching processing. The employment of the ESC in etcher system could make 8% enhancement of the wafer processing yield.

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Image Processing and Deep Learning-based Defect Detection Theory for Sapphire Epi-Wafer in Green LED Manufacturing

  • Suk Ju Ko;Ji Woo Kim;Ji Su Woo;Sang Jeen Hong;Garam Kim
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.2
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    • pp.81-86
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    • 2023
  • Recently, there has been an increased demand for light-emitting diode (LED) due to the growing emphasis on environmental protection. However, the use of GaN-based sapphire in LED manufacturing leads to the generation of defects, such as dislocations caused by lattice mismatch, which ultimately reduces the luminous efficiency of LEDs. Moreover, most inspections for LED semiconductors focus on evaluating the luminous efficiency after packaging. To address these challenges, this paper aims to detect defects at the wafer stage, which could potentially improve the manufacturing process and reduce costs. To achieve this, image processing and deep learning-based defect detection techniques for Sapphire Epi-Wafer used in Green LED manufacturing were developed and compared. Through performance evaluation of each algorithm, it was found that the deep learning approach outperformed the image processing approach in terms of detection accuracy and efficiency.

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The Electric Control Method on the Packaging Technology for Non-Conductive Materials Using the Surface Processing Cavity Pressure Sensor (표면 가공형 캐비티 압력센서를 이용하여 비전도성 물질용 패키지 기술에 전기적 제어방식 연구)

  • Lee, Sun-Jong;Woo, Jong-Chang
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.33 no.5
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    • pp.350-354
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    • 2020
  • In this study, a pressure sensor for each displacement was fabricated based on the silicon-based pressure sensor obtained through simulation results. Wires were bonded to the pressure sensor, and a piezoresistive pressure sensor was inserted into the printed circuit board (PCB) base by directly connecting a micro-electro-mechanical system (MEMS) sensor and a readout integrated circuit (ROIC) for signal processing. In addition, to prevent exposure, a non-conductive liquid silicone was injected into the sensor and the entire ROIC using a pipette. The packaging proceeded to block from the outside. Performing such packaging, comparing simple contact with strong contact, and confirming that the measured pulse wavelength appears accurately.

High Quality Vertical Silicon Channel by Laser-Induced Epitaxial Growth for Nanoscale Memory Integration

  • Son, Yong-Hoon;Baik, Seung Jae;Kang, Myounggon;Hwang, Kihyun;Yoon, Euijoon
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.14 no.2
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    • pp.169-174
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    • 2014
  • As a versatile processing method for nanoscale memory integration, laser-induced epitaxial growth is proposed for the fabrication of vertical Si channel (VSC) transistor. The fabricated VSC transistor with 80 nm gate length and 130 nm pillar diameter exhibited field effect mobility of $300cm^2/Vs$, which guarantees "device quality". In addition, we have shown that this VSC transistor provides memory operations with a memory window of 700 mV, and moreover, the memory window further increases by employing charge trap dielectrics in our VSC transistor. Our proposed processing method and device structure would provide a promising route for the further scaling of state-of-the-art memory technology.

A Design and study on automatic extraction of kernel data structure to improve performance of rootkit detection tool, Gibraltar. (루트킷 탐지 도구(Gibraltar) 성능 향상을 위한 자동화된 커널 메모리 자료 구조 추출에 관한 연구)

  • Choi, Wonha;Yi, Hayoon;Cho, Yeongpil;Paek, Yunheung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.04a
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    • pp.384-387
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    • 2015
  • 하이퍼바이저를 이용한 가상화 검사(Virtual Machine Introspection)의 하나인 Gibraltar[2]는 자동으로 무결성 명세서를 생성할 수 있고, 보안 위협이 높아지고 있는 데이터 영역에 대해서도 방어가 가능하다는 점에 존재하는 어떤 보안 도구보다 효과적인 시스템으로 여겨지고 있다. 본 연구에서는 루트킷 탐지 도구인 Gibraltar를 Linux/ARM 3.14 버전에서 구현하고, 커널 메모리 자료 구조 추출 자동화 툴을 개발함으로써 기존 연구의 문제점을 해결하여 성능을 개선하였다. 이를 바탕으로 향후 Gibraltar 연구의 추가 개선 방향을 제시한다.

A Survey on Deep Learning-Based Vulnerability Detection Technique (딥러닝 기반 취약점 탐색 기술에 대한 조망)

  • Kim, Hyun-Jun;Ahn, Sun-woo;Ahn, Seong-gwan;Paek, Yun-Heung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.198-201
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    • 2022
  • 본 논문에서는 소프트웨어에 내장된 취약점의 패턴을 인식하여 찾아내는 딥러닝 기반 취약점 탐색 기술에 대해 소개한다. 특정 소프트웨어의 소스 코드 혹은 바이너리 코드를 분석하여 취약점을 찾아내는 여러 기법들을 살펴본 다음, 딥러닝 기반 바이너리 취약점 탐색 기술의 향후 연구 방향을 조망하고자 한다.

Realization of Homomorphic Encrypted Deep Learning Models (동형암호를 활용한 딥러닝 모델 학습에 대한 연구)

  • Nam, Kevin;Cho, Myunghyun;Kim, Hyunjun;Paek, Yunheung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.113-116
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    • 2021
  • 동형암호를 활용한 딥러닝 시도가 꾸준히 이루어지고 있다. 딥러닝 모델에는 비선형함수가 활용되고 연산량이 점점 많아지는 추세지만, 이러한 점들은 동형암호 연산의 대표적인 제한사항들이다. 이러한 제한점들을 극복할 수 있는 방안들을 소개하며 그 근거를 간단한 실험들을 통해 증명하여 동형암호 딥러닝 모델 설계를 위한 가이드라인을 제공한다.

A Study of AI model extraction attack and defense techniques (AI 모델 탈취 공격 및 방어 기법들에 관한 연구)

  • Jun, So-Hee;Lee, Young-Han;Kim, Hyun-Jun;Paek, Yun-Heung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.382-384
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    • 2021
  • AI (Artificial Intelligence)기술이 상용화되면서 최근 기업들은 AI 모델의 기능을 서비스화하여 제공하고 있다. 하지만 최근 이러한 서비스를 이용하여 기업이 자본을 투자해 학습시킨 AI 모델을 탈취하는 공격이 등장하여 위협이 되고 있다. 본 논문은 최근 연구되고 있는 이러한 모델 탈취 공격들에 대해 공격자의 정보를 기준으로 분류하여 서술한다. 또한 본 논문에서는 모델 탈취 공격에 대응하기 위해 다양한 관점에서 시도되는 방어 기법들에 대해 서술한다.

A Study on the Application of Artificial Intelligence in Symbolic Execution: Usage in fuzzing and vulnerability detection (기호 실행에서의 인공 지능 적용에 대한 연구: 퍼징과 취약점 탐지에서의 활용)

  • Ha, Whoi Ree;Ahn, Sunwoo;Kim, Hyunjun;Paek, Yunheung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.05a
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    • pp.582-584
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    • 2020
  • 기호 실행 (symbolic execution)은 프로그램을 특정 상태로 구동하는 입력 값을 찾는 코드 분석기법이다. 이를 사용하면 자동화 소프트웨어 테스트 기법인 퍼징 (fuzzing)을 훨씬 효율적으로 사용하여 더 많은 보안 취약점을 찾을 수 있지만, 기호 실행의 한계점으로 인하여 쉽게 적용할 수 없었다. 이를 해결하기 위해 인공 지능을 활용한 방법을 소개하겠다.