• Title/Summary/Keyword: Error Check Algorithm

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Recurrent Neural Network Modeling of Etch Tool Data: a Preliminary for Fault Inference via Bayesian Networks

  • Nawaz, Javeria;Arshad, Muhammad Zeeshan;Park, Jin-Su;Shin, Sung-Won;Hong, Sang-Jeen
    • Proceedings of the Korean Vacuum Society Conference
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    • 2012.02a
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    • pp.239-240
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    • 2012
  • With advancements in semiconductor device technologies, manufacturing processes are getting more complex and it became more difficult to maintain tighter process control. As the number of processing step increased for fabricating complex chip structure, potential fault inducing factors are prevail and their allowable margins are continuously reduced. Therefore, one of the key to success in semiconductor manufacturing is highly accurate and fast fault detection and classification at each stage to reduce any undesired variation and identify the cause of the fault. Sensors in the equipment are used to monitor the state of the process. The idea is that whenever there is a fault in the process, it appears as some variation in the output from any of the sensors monitoring the process. These sensors may refer to information about pressure, RF power or gas flow and etc. in the equipment. By relating the data from these sensors to the process condition, any abnormality in the process can be identified, but it still holds some degree of certainty. Our hypothesis in this research is to capture the features of equipment condition data from healthy process library. We can use the health data as a reference for upcoming processes and this is made possible by mathematically modeling of the acquired data. In this work we demonstrate the use of recurrent neural network (RNN) has been used. RNN is a dynamic neural network that makes the output as a function of previous inputs. In our case we have etch equipment tool set data, consisting of 22 parameters and 9 runs. This data was first synchronized using the Dynamic Time Warping (DTW) algorithm. The synchronized data from the sensors in the form of time series is then provided to RNN which trains and restructures itself according to the input and then predicts a value, one step ahead in time, which depends on the past values of data. Eight runs of process data were used to train the network, while in order to check the performance of the network, one run was used as a test input. Next, a mean squared error based probability generating function was used to assign probability of fault in each parameter by comparing the predicted and actual values of the data. In the future we will make use of the Bayesian Networks to classify the detected faults. Bayesian Networks use directed acyclic graphs that relate different parameters through their conditional dependencies in order to find inference among them. The relationships between parameters from the data will be used to generate the structure of Bayesian Network and then posterior probability of different faults will be calculated using inference algorithms.

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A Study on Smart Ground Resistance Measurement Technology Based on Aduino (아두이노 기반 IT융합 스마트 대지저항 측정 기술 연구)

  • Kim, Hong Yong
    • Journal of the Society of Disaster Information
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    • v.17 no.4
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    • pp.684-693
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    • 2021
  • Purpose: The purpose is to establish a safe facility environment from abnormal voltages such as lightning by developing a smart land resistance measuring device that can acquire real-time land resistance data using Arduino. Method: This paper studied design models and application cases by developing a land resistance acquisition and analysis system with Arduino and a power line communication (PLC) system. Some sites in the wind power generation complex in Gyeongsangnam-do were selected as test beds, and real-time land resistance data applied with new technologies were obtained. The electrode arrangement adopted a smart electrode arrangement using a combination of a Wenner four electrode arrangement and a Schlumberger electrode arrangement. Result: First, the characteristic of this technology is that the depth of smart multi-electrodes is organized differently to reduce the error range of the acquired data even in the stratigraphic structure with specificity between floors. Second, IT convergence technology was applied to enable real-time transmission and reception of information on land resistance data acquired from smart ground electrodes through the Internet of Things. Finally, it is possible to establish a regular management system and analyze big data accumulated in the server to check the trend of changes in various elements, and to model the optimal ground algorithm and ground system design for the IT convergence environment. Conclusion: This technology will reduce surge damage caused by lightning on urban infrastructure underlying the 4th industrial era and design an optimized ground system model to protect the safety and life of users. It is also expected to secure intellectual property rights of pure domestic technology to create jobs and revitalize our industry, which has been stagnant as a pandemic in the post-COVID-19 era.

Implementation of a Mixing-Ratio Control System for Two-Component Liquid Silicone Mixture (이액형 액상실리콘 재료의 혼합비율 제어 시스템 개발)

  • Choo, Seong-Min;Kim, Young-Min;Lee, Keum-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.688-694
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    • 2018
  • The mixture ratio of two-component liquid silicone is important for the inherent physical characteristics of the finished product. Therefore, it is necessary to uniformly control the ratio of the main material and the sub-material. In this paper, a mixing-ratio control system was designed, which consists of a digital flow meter and a flow control system to measure the flow rate of the raw materials and a pumping system to maintain constant pressure and transfer of the raw materials. In addition, a program was developed to control the organic interlocking and mixing ratio. For the verification of the developed system, we compared the actual weight of raw material with the value measured by the flow meter during pumping, and we measured the physical properties of the mixed material by making test samples with and without the application of the mixing-ratio improvement algorithm. The measured value was close to the reference value with a hardness range of 46-47 and tensile strength of 9.3-9.5 MPa. These results show that the mixing ratio of the liquid silicone is controlled within an error range of ${\pm}0.5%$.

A Study on the Applicability of the Crack Measurement Digital Data Graphics Program for Field Investigations of Buildings Adjacent to Construction Sites (건설 현장 인접 건물의 현장 조사를 위한 균열 측정 디지털 데이터 그래픽 프로그램 적용 가능성에 관한 연구)

  • Ui-In Jung;Bong-Joo Kim
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.12 no.1
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    • pp.63-71
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    • 2024
  • Through the development of construction technology, various construction projects such as redevelopment projects, undergrounding of roads, expansion of subways, and metro railways are being carried out. However, this has led to an increase in the number of construction projects in existing urban centers and neighborhoods, resulting in an increase in the number of damages and disputes between neighboring buildings and residents, as well as an increase in safety accidents due to the aging of existing buildings. In this study, digital data was applied to a graphics program to objectify the progress of cracks by comparing the creation of cracks and the increase in length and width through photographic images and presenting the degree of cracks numerically. Through the application of the program, the error caused by the subjective judgment of crack change, which was mentioned as a shortcoming of the existing field survey, was solved. It is expected that the program can be used universally in the building diagnosis process by improving its reliability if supplemented and improved in the process of use. As a follow-up study, it is necessary to apply the extraction algorithm of the digital graphic data program to calculate the length and width of the crack by itself without human intervention in the preprocessing work and to check the overall change of the building.

Development and Performance Evaluation of Multi-sensor Module for Use in Disaster Sites of Mobile Robot (조사로봇의 재난현장 활용을 위한 다중센서모듈 개발 및 성능평가에 관한 연구)

  • Jung, Yonghan;Hong, Junwooh;Han, Soohee;Shin, Dongyoon;Lim, Eontaek;Kim, Seongsam
    • Korean Journal of Remote Sensing
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    • v.38 no.6_3
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    • pp.1827-1836
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    • 2022
  • Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.