• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.485-486
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• 2006

• 한국에너지공학회:학술대회논문집
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• 한국에너지공학회 1995년도 추계학술발표회 초록집
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• pp.75-81
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• 1995

DYLAM and its related applications are reviewed in detail and found to have many favourable characteristics. Concerning human factor analysis, the study demonstrates that DYLAM methodology represents an appropriate tool to study man-machine behaviour provided that DYLAM is used to model machine behaviour and an appropriate operator interface human factor model is included. A hybrid model which is a synthesis of the DYLAM model, a system thermodynamic simulation model and a neural network predicative model, is implemented and used to analyse dynamically the CANDU pressurizer system.

• 한국산업경영시스템학회:학술대회논문집
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• 한국산업경영시스템학회 2002년도 춘계학술대회
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• pp.403-412
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• 2002

Machine condition diagnosis is the technique to perceive the machine errors and the abrasion online without overhaul. We need the steps to predict the life span and reliability of a machine for the abrasion as with perceiving the degree of the abrasion of certain machine parts to make errors. In this study we deals with the methods to check and manage periodically and to configure the judgement criteria for the state of a machine. For the applications of CDT(Condition Diagnosis Technique) we also suggest the methods to check comparing the measured vibration values with the absolute criteria and to check the abnormality by vibration level.

• Nuclear Engineering and Technology
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• 제49권2호
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• pp.404-410
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• 2017

In order to help decision-makers in the early design phase to improve and make more cost-efficient system safety and reliability baselines of aircraft design concepts, a method (Multi-objective Optimization for Safety and Reliability Trade-off) that is able to handle trade-offs such as system safety, system reliability, and other characteristics, for instance weight and cost, is used. Multi-objective Optimization for Safety and Reliability Trade-off has been developed and implemented at SAAB Aeronautics. The aim of this paper is to demonstrate how the implemented method might work to aid the selection of optimal design alternatives. The method is a three-step method: step 1 involves the modelling of each considered target, step 2 is optimization, and step 3 is the visualization and selection of results (results processing). The analysis is performed within Architecture Design and Preliminary Design steps, according to the company's Product Development Process. The lessons learned regarding the use of the implemented trade-off method in the three cases are presented. The results are a handful of solutions, a basis to aid in the selection of a design alternative. While the implementation of the trade-off method is performed for companies, there is nothing to prevent adapting this method, with minimal modifications, for use in other industrial applications.

• 한국신뢰성학회지:신뢰성응용연구
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• 제5권1호
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• pp.181-192
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• 2005

In this paper, we consider a process for design for reliability(DFR) in design and development phases. The procedure of GE for DFR is applied to develope and analyze a washing machine with required reliability and the detailed procedure is proposed.

• 한국신뢰성학회지:신뢰성응용연구
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• 제13권3호
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• pp.175-190
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• 2013

This study considers reliability growth management as the excellent method for construction equipment development with the effect on decreasing COPQ(Cost of Poor Quality Cost) of new products. MIL-HDBK-189A(1981) and RADC-TR-84-20(1984) standards provide a general concept of reliability growth management including to reliability growth test, models and FRACAS(Failure Reporting and Corrective Action System). There is no study how to apply reliability growth management to construction equipment(or machine) development. This paper propose the method to apply it to construction equipment development process from the reliability target setting for developing products to launching them at market. It is expecially showing how to set target reliability for new developing equipment and the development risk to reach the reliability target in detail.

• 융합보안논문지
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• 제22권3호
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• pp.101-110
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• 2022

다양한 분야에서 인공지능을 활용한 사례가 증가하면서 침입탐지 분야 또한 다양한 이슈를 인공지능을 통해 해결하려는 시도가 증가하고 있다. 하지만, 머신러닝을 통한 예측된 결과에 관한 이유를 설명하거나 추적할 수 없는 블랙박스 기반이 대부분으로 이를 활용해야 하는 보안 전문가에게 어려움을 주고 있다. 이러한 문제를 해결하고자 다양한 분야에서 머신러닝의 결정을 해석하고 이해하는데 도움이 되는 설명 가능한 AI(XAI)에 대한 연구가 증가하고 있다. 이에 본 논문에서는 머신러닝 기반의 침입탐지 예측 결과에 대한 신뢰성을 강화하기 위한 설명 가능한 AI를 제안한다. 먼저, XGBoost를 통해 침입탐지 모델을 구현하고, SHAP을 활용하여 모델에 대한 설명을 구현한다. 그리고 기존의 피처 중요도와 SHAP을 활용한 결과를 비교 분석하여 보안 전문가가 결정을 수행하는데 신뢰성을 제공한다. 본 실험을 위해 PKDD2007 데이터셋을 사용하였으며 기존의 피처 중요도와 SHAP Value에 대한 연관성을 분석하였으며, 이를 통해 SHAP 기반의 설명 가능한 AI가 보안 전문가들에게 침입탐지 모델의 예측 결과에 대한 신뢰성을 주는데 타당함을 검증하였다.

• 한국정밀공학회지
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• 제23권6호
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• pp.111-118
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• 2006

Recently, the reliability evaluation and analysis are applied far many industrial products which are required to guarantee in quality and efficiency. The purpose of this paper is to present some of reliability evaluation methodologies that are applicable to machine tools. Especially ATC (Automatic Tool Changer), which is a core component of line center, was chosen as the target of the reliability evaluation and analysis. The scope of research is reliability prediction, reliability test and evaluates their results. The results of reliability evaluation have shown the failure rates, MTBF (Mean Time Between Failure), reliability for those components of ATC and real tests reliability through the constructed reliability test-bed. It is expected that proposed methodologies would increase reliability for a high-speed line center.

• International journal of advanced smart convergence
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• 제12권2호
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1914-1917
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• 2005

Recently, the reliability evaluation and analysis are applied for many industrial products, and many products are required to guarantee in quality and in efficiency. The purpose of this paper is to present some of reliability evaluation methodologies that are applicable to machine tools. Especially ATC(Automatic Too Changer), which is core component of line center, was chosen as the target of the reliability evaluation and analysis. The scope of research is reliability prediction, reliability test and evaluates their results. The results of this research has shown the failure rate, MTBF(Mean Time Between Failure), reliability for those components and real tests reliability through constructed reliability test-bed. It is expected that proposed methodologies will increase reliability for high speed line center.