• Proceedings of the Korean Institute of Industrial Safety Conference
• /
• 1997.05a
• /
• pp.51-54
• /
• 1997

방독마스크 수명예측을 위하여는 여러 모델식이 제안되었으며, Cohen등은 bed-residence 흡착 모델을 사용하여 정화통에서 채취한 활성탄을 carbon tube에 bed-residence time이 같게 충전시켜 습도에 따른 정화통의 수명을 예측하였다. 그리고, Mover는 Potential Jonas 모델을 적용하여 환경적 조건들과 아세톤에 대하여 유기증기 정화통의 특성을 묘사하였다. (중략)

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.40 no.3
• /
• pp.259-265
• /
• 2016

Recently, life prediction models for Pb-based and Pb-free solders used in chip resistor assemblies under thermal cycling have been introduced. The models suggest that the field lifetimes of Pb-free solders would be better than those of Pb-based solders when used for chip resistors under thermal cycling conditions, while the lifetime of the chip assemblies under accelerated test conditions show a reverse relationship. In this study, the prediction models were verified by applying the model to another research case. Finite element models were built, thermal cycling conditions were applied, and the energy densities were calculated. Finally, life prediction analysis was conducted for the cases where Pb-based and Pb-free solders were used. The prediction results were then compared with the test data of the case. It was verified that the predictions of the developed life cycle models are on the practical scale.

• Annual Conference of KIPS
• /
• 2020.11a
• /
• pp.978-981
• /
• 2020

제품이나 부품의 잔존 수명을 정확하게 예측할 수 있다면 고장이나 중단으로 인한 손실을 방지하는 것이 가능해질 것이다. 제품의 잔존 수명은 시계열 데이터 분석을 통해 예측될 수 있으며, 최근에는 딥러닝을 이용한 잔존 수명 예측 연구가 활발하게 진행되고 있다. 본 연구에서 우리는 컴퓨터 기반 시스템의 주요 고장 요소가 되고 있는 하드디스크의 잔존 수명을 예측하는 문제에 1D CNN-LSTM 을 이용한 모델을 적용하고, RMSE 와 R-Square 값을 이용해 적용한 모델의 성능을 평가하였다.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.4
• /
• pp.457-465
• /
• 2010

In this study, a Taylor series (T-S) model based on the Arrhenius, McVetty, and Monkman-Grant equations was developed using a mathematical analysis. In order to reduce fitting errors, the McVetty equation was transformed by considering the first three terms of the Taylor series equation. The model parameters were accurately determined by a statistical technique of maximum likelihood estimation, and this model was applied to the creep data of alloy 617. The T-S model results showed better agreement with the experimental data than other models such as the Eno, exponential, and L-M models. In particular, the T-S model was converted into an isothermal Taylor series (IT-S) model that can predict the creep strength at a given temperature. It was identified that the estimations obtained using the converted ITS model was better than that obtained using the T-S model for predicting the long-term creep life of alloy 617.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.16 no.6
• /
• pp.533-542
• /
• 2014

In this study TBM disc cutter prediction models including Gehring, CSM and NTNU models were investigated and the characteristics of the models were examined. The influence of penetration, uniaxial compressive strength and abrasiveness index on the models was analyzed. The life of disc cutter linearly increases with penetration per revolution and decreases with increasing uniaxial compressive strength of rocks. As the abrasiveness index, CAI, increases, the life of disc cutter in Gehring and CSM model decreases. On the contrary, the life of disc cutter life in NTNU model decreases with increasing CLI. Also, comparisons of predicted disc life were made between models using actual job site data.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.5D
• /
• pp.453-461
• /
• 2012

Life analysis is conducted for economic analysis of equipment or facilities. The purpose of life analysis is to predict future indicators for scrapping construction equipment, and establish and utilize a wide variety of business strategies according to data predictions. First, this study shows the methods to figure out average life, life expectancy and life prediction of construction equipment and the analysis of life making methods, using survival curves. Second, the study proposes and examines the life expectancy making model depending on revenues and expenses. The result of the study reveals that the economic life of the same equipment varies with expenses, revenues and the initial cost. The life expectancy making model for construction equipment reflects respective management status for equipment and will help efficient management for companies.

• Proceedings of the Korean Institute of Surface Engineering Conference
• /
• 2009.10a
• /
• pp.233-234
• /
• 2009

증착된 silicon nitride (Sin) 박막의 수명 시간을 예측하는 신경망 모델을 개발하였다. SiN 박막은 플라즈마 화학기상 증착방식을 이용하여 증착되었다. 증착 공정은 통계적인 실험계획표를 이용하여 수행되었고, 신경망 모델의 예측 성능은 유전자 알고리즘을 이용하여 최적화하였다. 수명시간은 다른 박막특성 (굴절률, 증착률, 전하밀도)의 영향을 상당히 받았으며, 특히 굴절률과 전하밀도는 높은 증착률에서 증가시킬 때 수명시간을 최대화할 수 있었다.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.15 no.5
• /
• pp.1455-1461
• /
• 1991

본 연구에서는 Kachanov의 재료손상(material damage)모델을 이용하여 새로운 수명예측식을 만들고, 이 수명예측식의 타당성을 조사하기 위하여, 최근에 발표된 크 립 수명과 기공분포와의 실험결과와 비교하였다.

• Journal of Korea Society of Industrial Information Systems
• /
• v.29 no.5
• /
• pp.51-68
• /
• 2024

To safely operate lithium-ion batteries that power mobile electronic devices, it is crucial to accurately predict the remaining useful life (RUL) of the battery. Recently, with the advancement of machine learning technologies, artificial intelligence (AI)-based RUL prediction models for batteries have been actively researched. However, existing models have limitations as the reasoning process within the models is not transparent, making it difficult to fully trust and utilize the predicted values derived from machine learning. To address this issue, various explainable AI techniques have been proposed, but these techniques typically visualize results in the form of graphs, requiring users to manually analyze the graphs. In this paper, we propose an explainable RUL prediction method for lithium-ion batteries that interprets the reasoning process of the prediction model in textual form using SHAP analysis based on large language models (LLMs). Experimental results using publicly available lithium-ion battery datasets demonstrated that the LLM-based SHAP analysis enabled us to concretely understand the model's prediction rationale in textual form.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.39 no.12
• /
• pp.1107-1114
• /
• 2011

In this paper, the fatigue life of a laser peened structure was predicted. In order to calculate residual stress induced by laser peening finite element simulation was carried out. Modified Goodman equation was used to consider the effect of compressive residual stress induced by laser peening in fatigue analysis. In addition, additive adjustment factor approach was applied to consider S-N curve model uncertainty. Consequently, the reliable bounds of the predicted fatigue life of the laser peened structure was determined.