• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.213-221
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• 2022

Defects are the risk factors in the construction process of buildings. They cause damage, delaying the construction duration. They especially cause adverse effects on the top-down construction method. This study analyzed the degree of construction delay induced by each work type, focusing on defects in the top-down method. Then, we derived construction delay induction coefficient from different work types in order by using the severity of construction delay per defect and the occurrence probability of defect; this assessment model measures the impact of defects on construction delay for each work type. Furthermore, by comparing each work type based on the defect frequency and the construction delay induction coefficient, we found work types that need to be administered attentively. We identified that plastering work was easy to overlook, requiring caution in defect management. This study provides an efficient defect management system suitable for the buildings that are built using the top-down construction method.

• 대한산업공학회지
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• 제21권3호
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• pp.371-385
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• 1995

The yield of semiconductor chips is dependent not only on the average defect density but also on the distribution of defects over a wafer. The distribution of defects leads to consider a cluster index. This paper briefly reviews the existing yield prediction models ad proposes a new cluster index, which utilizes the information about the defect location on a wafer in terms of the coefficient of variation. An extensive simulation is performed under a variety of defect distributions and a yield prediction model is derived through the regression analysis to relate the yield with the proposed cluster index and the average number of defects per chip. The performance of the proposed simulation-based yield prediction model is compared with that of the well-known negative binomial model.

• 비파괴검사학회지
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• 제23권6호
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• pp.622-634
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• 2003

This paper is concerned with a computational method for recovering a crack shape of steam generator tubes of nuclear plants. Problems on the shape identification are discussed arising in the characterization of a structural defect in a conductor using data of eddy current inspection. A surface defect on the generator tube ran be detected as a probe impedance trajectory by scanning a pancake type coil. First, a mathematical model of the inspection process is derived from the Maxwell's equation. Second, the input and output relation is given by the approximate model by virtue of the hybrid use of the finite element and boundary element method. In that model, the crack shape is characterized by the unknown coefficients of the B-spline function which approximates the crack shape geometry. Finally, a parameter estimation technique is proposed for recovering the crack shape using data from the probe coil. The computational experiments were successfully tested with the laboratory data.

• Nuclear Engineering and Technology
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• 제23권3호
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• pp.321-327
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• 1991

가돌리니아 첨가 우라니아에 대한 점결함 모델이 순수 우라니아의 점결함구조를 바탕으로 하여 개발되었다. Gd 도펀트는 금속이온자리에 -1 유효전하를 지니고, 주위의 산소침입형을 밀어내어 산소침입형의 자리를 감소시킨다. 산소 공공 농도가 증가하면 Gd 도펀트는 산소공공과 집합체를 형성하게 된다. 이 점결함 모델은 Gd 도펀트의 양의 증가에 따른 산소포텐샬의 증가와 산소 대금추비율이 2일때 급속한 산소포텐샬 변화를 설명하여, 현존하는 실험값과 좋은 일치를 보였다.

• 한국산학기술학회논문지
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• 제9권6호
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• pp.1614-1618
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• 2008

본 논문은 레이아웃 수정에 따른 수율차 계산을 위한 새로운 모델을 제안한다. 패턴 사이의 빈 공간의 크기를 늘리거나 줄이는 레이아웃 변경으로 인한 결함 평균치의 차를 구하기 위한 식이 단락 결함과 개방 결함에 대해 제시 되었다. 미세 패턴인 조그를 포함한 구부러진 연결선등을 가지는 복잡한 레이아웃 변경은 패턴을 작은 조각으로 쪼개고 패턴 사이의 공간과 패턴의 폭을 재정의 함으로써 새롭게 모델링 하였다. 이 모델은 레이아웃 변경에 의한 수율 변화와 결함 제한적 수율에 대한 비용함수 모니터링을 쉽게 할 수 있다는 장점을 갖는다.

• 대한전자공학회논문지TC
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• 제41권8호
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• pp.69-78
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• 2004

본 논문은 Malaiya와 denton이 제안한 모듈크기(module size)와 소프트웨어 결함밀도와의 관계를 확률 모델화하는데 있어서 고려할 사항으로 정확한 소프트웨어 결함밀도를 추정하는데 그 목적이 있다. 구체적으로 말하면 우리가 수행한 3개 프로젝트에 대해서 지수형 분포 및 기하분포 등에 대한 소프트웨어 모듈의 크기 분포나 모듈 또는 tan 등 규정된 크기에서 포함하고 있는 결함수를 추정하고 실측데이터에 적합한 모델의 구성 가능성을 제안하여 시험기간 중에 관측된 데이터를 적용하여 이를 상호 비교한다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 가을 학술논문 발표대회
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• pp.223-224
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• 2022

The occurrence of defect, one of the major risk elements, gives rise to construction delays and additional costs. Although construction companies generally prefer to use a method of identifying and classifying the causes of defects, a system for predicting the rise of defects becomes important matter to reduce this harmful issue. However, the currently used methods are kinds of reactive systems that are focused on the defects which occurred already, and there are few studies on the occurrence of defects with prediction systems. This paper is about preliminary study on the development of judgemental algorithm that informs us whether additional works related to defect issue are needed or not. Among machine learning techniques, deep neural network was utilized as prediction model which is a major component of algorithm. It is the most suitable model to be applied to the algorithm when there are 8 hidden layers and the average number of nodes in each hidden layer is 70. Ultimately, the algorithm can identify and defects that may arise in later and contribute to minimize defect frequency.

• 소성∙가공
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• 제31권4호
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• pp.229-239
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• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.

• 대한기계학회논문집A
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• 제29권2호
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• pp.253-261
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• 2005

In decades, a substantial body of work on a unified viscoplastic model which considers the mechanism of plastic deformation and creep deformation has developed. The systematic scheme for numerical analysis of unified model is necessary because the dominant failure mechanism is the defect growth and coalescence in materials. In the present study, the unified viscoplastic model for materials with defects suggested by Suquet and Michel was employed for numerical analysis. The constitutive equations are integrated based on the generalized mid-point rule and implemented into a finite element program (ABAQUS) by means of user-defined subroutine (UMAT). To evaluate the validity of the developed UMAT code and the assessment of the adopted viscoplastic model, the results obtained from the UMAT code was compared with the numerical reference solution and experimental data. The unit cell analysis also has been investigated to study the effect of strain rate, temperature, stress triaxiality and initial defect volume fraction on the growth and coalescence of the defect.

• Imaging Science in Dentistry
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• 제34권1호
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• pp.35-48
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• 2004

Purpose: To investigate the effect of rhBMP-2 on the healing of bone defect in the low calcium diet rat. Materials and Methods: To prepare the experimental model, control group was fed a normal diet and experimental group was fed a low calcium diet for 3 weeks. And then, 4 mm bicortical perforated bone defect was made on mandibular body of each rats. Experimental group was subdivided into two groups; experimental group 1 (rats given a low calcium diet before and after bone defect) and experimental group 2 (rats given a low calcium diet before and after bone defect with rhBMP-2 application). At 1, 3, 5 and 7 weeks after bone defect formation, the rats were terminated. The healing of bone defect was assessed by three-dimensional computerized tomography, soft x-ray radiography, and histopathological examination. Results : The wound healing of the bone defect for control group, experimental group 1, and experimental group 2 showed a increase from 3 weeks after bone defect formation. The experimental group 2 showed a more increase in healing amount than control group and experimental group 1 from 5 weeks after bone defect formation and the experimental group 2 showed a complete recovery of bone defect at 7 weeks after bone defect formation. Conclusion: The healing process of bone defect is accelerated by rhBMP-2 application in the low calcium diet rats.