• 산업경영시스템학회지
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• 제32권2호
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• 한국산학기술학회논문지
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• 제8권5호
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• pp.1082-1086
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• 2007

본 연구는 국내에서 발생되는 소각재를 재활용하여 벽돌 생산을 하는 공장에서의 이원화된 작업현황을 일원화 할 수 있는 데이터 모니터링 시스템 구축을 목적으로 한다. 모니터링 시스템은 상태관리 프로세스, 위치관리 프로세스, 불량관리 프로세스, 상황관리 프로세스 등의 데이터 관리 프로세스를 이용해 데이터를 자동 관리하도록 설계하였다. 본 연구에서는 RFID 태그를 이용하여 각 공정의 상황 정보를 수집하고 수집된 정보를 가공하여 데이터 모니터링 시스템에 전송한다. 이러한 시스템을 통해 분석된 데이터는 소각재를 재활용하여 벽돌 생산을 하는 공장에서 공정자동화, 불량률 최소화, 실시간 모니터링, 적재 관리를 통해 생산 공정을 효율적으로 관리할 수 있다.

• 한국과학예술포럼
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• 제37권3호
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• pp.125-134
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• 2019

본 연구는 영상콘텐츠 제작과정에서 배경음악 선정의 자동화를 위하여 영상의 특성을 분류, 분석할 수 있는 프로그램을 구성하였다. 연구 결과 및 내용은 다음과 같다. 영상의 특성은 '주제 범주', '감정', '픽셀 움직임 속도', '색상', '등장인물' 로 선정하며, '주제 범주'와 '감정'은 Microsoft사의 Azure Video Indexer를, '픽셀 움직임 속도'는 Optical flow, '색상'은 Image Histogram, '등장인물'은 CNN (Convolutional Neural Network)을 활용하여 데이터를 추출하였다. 이러한 본 연구의 결과는 최근 주목을 받고있는 '인터넷 1인 방송 크리에이터'들의 콘텐츠 제작과정에서 배경음악 매칭을 위한 영상 특성 분석이 이루어졌다는 점에서 의의가 있다.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.87-92
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• 2021

Analysis of current state of construction industry functioning in Ukraine allows us to identify a number of problems having negative impact on sustainable development of construction industry, especially in terms of its organization. Therefore, it is absolutely essential to study existing methods of organization system supplying construction sites with necessary material resources. Companies can develop their own logistics departments, which independently solve logistics issues related to transportation organization and management, accounting and inventory management, acquisition and warehousing, intercommunication (ability to obtain both final and intermediate information during transporting materials). Using a complex of methods is substantiated: the hierarchy analysis method (Saati's method), the network method, the defect elimination algorithm DEA, the transportation problem that finds optimal problem solutions for construction sector with the purpose of rational supplying uninterrupted construction with building resources in the designed model "provider-transportation-costs".

• 대한방사성의약품학회지
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• 제8권1호
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• pp.3-8
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• 2022

Alteration of the mGluR5 density is closely related to various brain diseases including schizophrenia, depression, Parkinson's disease, and Alzheimer's disease. Therefore, mGluR5 is considered as a valuable imaging biomarker for brain disease and many radiopharmaceuticals have been developed so far. Among them, [¹⁸F]FPEB has favorable pharmacokinetic characteristics, and this is the most frequently used radiopharmaceutical for preclinical and clinical studies. In the present study, we want to introduce the optimized radiosynthetic method for the routine production of [¹⁸F]FPEB using a GE TRACERlabTM FXFN pro module. In addition, the entire process was monitored with a webcam to solve the problems arising from the synthetic process. As a result, [¹⁸F]FPEB was prepared by nucleophilic substitution from its nitro- precursor at 120℃ for 20 min in dimethyl sulfoxide. Radiochemical yield was 13.7 ± 5.1% (decay-corrected, n = 91) with the molar activity of 84 ± 17 GBq/µmol at the end of synthesis. The radiochemical purity was determined to be above 96%. The manufactured [¹⁸F]FPEB injection for quality controls were carried out in accordance with an KIRAMS approved protocol, as per ICH and USP guidelines.

• 반도체디스플레이기술학회지
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• 제22권3호
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• pp.62-66
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• 2023

With the advancement in technology and rapid increase in the demand for microelectromechanical systems (MEMS) based inertial measurement units (IMUs), high-volume production and test system remain a major challenge for the MEMS industry. To compete with the challenging market of Industry 4.0, here we developed an automatic test system to evaluate the performance of the ovenized IMU sensors as well as analyze the data. The automatic test system was developed by interfacing a commercial MEMS IMU (BMI 088) using LabVIEW. The BMI 088 was tested experimentally for long-term bias stability, ON/OFF bias repeatability, and root mean square (rms) noise. Furthermore, the data was analyzed through the developed test system. The results show that the automatic test system has improved the test time and reduced human effort. The developed automatic test system is a significant approach to MEMS research and development (R&D) to increase and improve the mass production of IMUs.

• Corrosion Science and Technology
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• 제23권2호
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• pp.131-138
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• 2024

This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 B
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• pp.1211-1214
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• 1992

본 논문에서 제안한 Fara DS Series의 AC SERVO (DC BRUSHLESS) MOTOR 제어기는 ROBOT, CNC, 각종 공작기계및 FA기기에서 MOTOR를 구동 원으로 사용하는데 사용되는 제품이다. AC SERVO MOTOR DRIVE의 Inverter에 IGBT(Insulated Gate Bipoler Transistor)를 사용하여 Switching 주파수를 높임으로써 Motor를 가변속 제어할때 발생하는 소음 및 진동을 극소화 하였다. 또한 일반적으로 Motor 속도제어를 급감속으로 제어할때 Servo Motor의 비선형 특성으로 인한 전류위상을 보상하여 모든 동작구간에서 최적의 상태의 제어가 되도록 개발하였다. 그리고 다양한 User Option 기능을 내장하여 User가 원하는 제어대상에 효과적으로 적용할 수 있도록 하였다. 아울러 MOTOR 제어기에 내장 된 다수의 보호기능을 통해서 Motor운전중 발생하는 이상상태에 대해 제어기를 보호할 수 있도록 하였다. 제안한 제어기는 부하변동, 전압변동, 온습도변동에 대해 속도변동율을 최소화 함으로써 ROBOT, CNC등 FA분야에서 폭넓게 이용할수 있다.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2000년도 제31회 춘계학술대회
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• pp.68-75
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• 2000

The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining system. A major topic relevant to metal-cutting operations is monitoring tool wear, which affects process efficiency and product quality, and implementing automatic tool replacements. In this paper, the measurement of the cutting force components has been found to provide a method for an in-process detection of tool wear. Cutting force components are divided into static and dynamic components in this paper, and the static components of cutting force have been used to detect flank wear. To eliminate the influence of variations in cutting conditions, tools, and workpiece materials, the force modeling is performed for various cutting conditions. The normalized force disparities are defined in this paper, and the relationships between normalized disparity and flank wear are established. Finally, Artificial neural network is used to learn these relationships and detect tool wear. According to the proposed method, the static force components could provide the effective means to detect flank wear for varying cutting conditions in turning operation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.137-140
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• 1996

Finding line segments in an intensity image has been one of the most fundamental issues in computer vision. In complex scenes, it is hard to detect the locations of point features. Line features are more robust in providing greater positional accuracy. In this paper we present a robust "line features extraction" algorithm which extracts line feature in a single pass without using any assumptions and constraints. Our algorithm consists of five steps: (1) edge scanning, (2) edge normalization, (3) line-blob extraction, (4) line-feature computation, and (5) line linking. By using edge scanning, the computational complexity due to too many edge pixels is drastically reduced. Edge normalization improves the local quantization error induced from the gradient space partitioning and minimizes perturbations on edge orientation. We also analyze the effects of edge processing, and the least squares-based method and the principal axis-based method on the computation of line orientation. We show its efficiency with some real images.al images.