• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1307-1310
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• 2005

ATM is element that reliability, stability is important in relation with customer by financial agency used device. To embody high reliability and stability, reliability estimation technology development is important. When new product is developed, performance and reliability evaluation of product are essential element. In this paper, is treating contents on reliability estimation of stepping motor, BLDC motor and solenoid that is main driving source of note handling units.

• Journal of Platform Technology
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• 제9권1호
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• pp.32-39
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• 2021

기존 환경측정기기는 전자파 및 친환경 제품 인증, 내구성 시험 위주이며, 센서 신뢰성 검증 및 측정 데이터에 대한 검증은 형식 승인 및 등록, 인수시험, 초기교정, 주기시험 등을 통해 센서 성능평가 위주로 수행된다. 본 플랫폼은 각 타겟 센서별 성능평가 뿐만 아니라 센서의 데이터 신뢰성에 대한 검증체계 지원 ICT 기반 환경 모니터링 센서 신뢰성 검증 체계를 구축하였다. 환경 정보에 대한 센서 데이터를 수집할 센서보드를 제작하였고 센서 및 데이터 신뢰성 평가 및 검증 서비스 체계를 규격화 하였다. 또한, ICT 기반 센서 데이터 신뢰성 평가 및 검증을 위해 LoRa 통신을 이용한 센서 데이터 플랫폼 모니터링 프로토타입을 제작하였고 이를 스마트 시티 등에 실증 테스트하였다. 해당 시스템을 통해 받은 데이터 분석을 위해 머신러닝을 이용하여 최적화 알고리즘 개발하였다. 이를 통해 신뢰성 검증을 위한 센서 빅데이터 분석시스템을 구축하였고 통합 평가 및 검증 시스템의 기반을 마련하였다.

• 한국기계가공학회지
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• 제11권4호
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• pp.147-153
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• 2012

The demands of the large scale machine tools, for instance, such as planomiller, turning machine, boring machine, NC machine, have been gradually increased in recent years. As the performances of machine tools and/or cutting tools are advanced, it is possible to perform high-speed and high-precision cutting works. The effective treatment of wet chip, which is discharged from cutting works, becomes very important problems. Therefore, this study is forced on the design of large scale machine tools using CATIA V5R18 and analysis of cutter, which is considered as essential equipment in large scale machine tools, using MSC.Nastran & MSC.Patran. Especially, the relations between tolerated load of cutter, driving horse power and rpm of driving shaft in chip processing system are investigated through analysis. As the results, the reliability of design could be improved by evaluating simulated numerical values, it showed that tolerated loads of supported part and edged part of cutter are 87,000N and 14,450N, respectively.

• Tribology and Lubricants
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• 제36권6호
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• pp.307-314
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• 2020

In this paper, studies on application cases of machine condition monitoring using oil sensors are reviewed. Owing to rapid industrial advancements, maintenance strategies play a crucial role in reducing the cost of downtime and improving system reliability. Consequently, machine condition monitoring plays an important role in maintaining operation stability and extending the period of usage for various machines. Machine condition monitoring through oil analysis is an effective method for assessing a machine's condition and providing early warnings regarding a machine's breakdown or failure. Among the three prevalent methods, the online analysis method is predominantly employed because this method incorporates oil sensors in real-time and has several advantages (such as prevention of human errors). Wear debris sensors are widely employed for implementing machine condition monitoring through oil sensors. Furthermore, various types of oil sensors are used in different machines and systems. Integrated oil sensors that can measure various oil attributes by incorporating a single sensor are becoming popular. By monitoring wear debris, machine condition monitoring using oil sensors is implemented for engines, automotive transmission, tanks, armored vehicles, and construction equipment. Additionally, such monitoring systems are incorporated in aircrafts such as passenger airplanes, fighter airplanes, and helicopters. Such monitoring systems are also employed in chemical plants and power plants for managing overall safety. Furthermore, widespread application of oil condition diagnosis requires the development of diagnostic programs.

• 한국인공지능학회지
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• 제11권4호
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• pp.29-34
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• 2023

The flow from developing a machine learning model to deploying it in a production environment suffers challenges. Efficient and reliable deployment is critical for realizing the true value of machine learning models. Bridging this gap between development and publication has become a pivotal concern in the machine learning community. FastAPI, a modern and fast web framework for building APIs with Python, has gained substantial popularity for its speed, ease of use, and asynchronous capabilities. This paper focused on leveraging FastAPI for deploying machine learning models, addressing the potentials associated with integration, scalability, and performance in a production setting. In this work, we explored the seamless integration of machine learning models into FastAPI applications, enabling real-time predictions and showing a possibility of scaling up for a more diverse range of use cases. We discussed the intricacies of integrating popular machine learning frameworks with FastAPI, ensuring smooth interactions between data processing, model inference, and API responses. This study focused on elucidating the integration of machine learning models into production environments using FastAPI, exploring its capabilities, features, and best practices. We delved into the potential of FastAPI in providing a robust and efficient solution for deploying machine learning systems, handling real-time predictions, managing input/output data, and ensuring optimal performance and reliability.

• Tribology and Lubricants
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• 제18권4호
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• pp.285-290
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• 2002

Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

• International Journal of Precision Engineering and Manufacturing
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• 제8권1호
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• pp.32-37
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• 2007

The outer diameter finishing grinding process required for ferrules, which are widely used as fiber optic connectors, is carried out by high-precision centerless grinding machines. In this study, the thermal characteristics of such a machine, for example, the temperature distribution, temperature rise, and thermal deformation, were estimated based on a virtual prototype and the heat generation rates of heat sources related to normal operating conditions. The prototype consisted of a concrete-filled bed. hydrostatic grinding wheel (GW) and regulating wheel (RW) spindle systems, a hydrostatic RW feed mechanism, a RW swivel mechanism, and on-machine GW and RW dressers. The reliability of the predicted results was demonstrated using temperature characteristics measured from a physical prototype. The predicted and measured results indicated that this particular high-precision centerless grinding machine had very stable thermal characteristics.

• 한국기계가공학회지
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• 제6권3호
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• pp.112-118
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• 2007

Recently, the machine tools called multi-task machines, which mounted rotary axes on the table or spindle are used increasingly. Accordingly, multi-task machine tool takes a growing interest on the motion accuracy of feed drive system. In this study, measurement and diagnosis of motion errors ware attempted from circular pattern obtained by using DBB (Double ball bar) device. Those were obtained at both clockwise and counter clockwise motions in mutually perpendicularly intersecting three planes. The reliability of error measurement system for multi-task machine tool was verified by the direct test cutting.

• 한국기계가공학회지
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• 제6권3호
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• pp.31-37
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• 2007

Recently, the machine tools called multi-task machines, which mounted rotary axes on the table or spindle are used increasingly. Accordingly, multi-task machine tool takes a growing interest on the motion accuracy of feed drive system. In this study, measurement and diagnosis of motion errors ware attempted from circular pattern obtained by using DBB (Double ball bar) device. Those were obtained at both clockwise and counter clockwise motions in mutually perpendicularly intersecting three planes. The reliability of error measurement system for multi-task machine tool was verified by the direct test cutting.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.169-172
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• 2000

In this paper, an OMM (On-the-Machine Measuring) system has been developed, which can perform measuring and inspection of sculptured surfaces of die and mold, by use of a scanning-type touch probe mounted into the spindle of a NC machine. The calibration procedures of a scanning prove (SP2-1, Renishaw) and an algorithm for measuring surface points by a ball-nosed stylus have been studied. The system has been developed based on commercial CAM software (Z-Master 2000), and tested through measuring a plastic injection molding-die. Also some experimental results of the calibration and measuring for given surface positions are analyzed to verify its accuracy and reliability.