• 산업경영시스템학회지
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• 제45권4호
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• pp.157-166
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• 2022

In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

• 한국안전학회지
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• 제30권5호
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• pp.52-58
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• 2015

Although lots of safety inspection and precision safety diagnosis have been conducted on concrete retaining wall, there is no comprehensive analysis on the basis of the accumulated data associated with the statistic. Especially, the concentrated management is necessary on the evaluation items that cause critical damages for the efficient performance. In this regard, this study conducted a correlation analysis between the 18 condition evaluation items and defect index for the concrete retaining wall as well as how each item affects the final defect index as much as in the manual. As a result, correlation coefficient between sliding and overturning was 0.601, which means that they have a strong correlation, and the most influential item on defect index is the condition of drainage that scored the 0.750 correlation coefficient. In addition, as a result of regression analysis, the condition of drainage with the 0.683 correlation coefficient has a strong correlation with the defect index. If the condition evaluation items are integrated or readjusted based on the results of the statistical analysis in this study, the more efficient and accurate maintenance will be possible.

• 비파괴검사학회지
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• 제30권3호
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• pp.261-270
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• 2010

This paper presents an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional side bands that contain the time-of-flight information on the defect location. One of the side band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free detection of a defect, so that experimental studies are needed to verify the proposed method and to be applied to real structure.

• Journal of the Korean Data and Information Science Society
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• 제19권2호
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

• 한국조경학회지
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• 제25권3호
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• pp.1-11
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• 1997

This study aims to estimate the relative importance of quality management items through the defect analysis in the landscape construction process. The RIQMI are decided by the defect coefficient and it's cause weight. The defect items in the landscape construction process were classified by 56 items based on the classification form of '96 landscape architectural construction standard and the cause pattern were categorized 4 types as design, material, construction, and environment factors. To analyze the defect coefficient and the aucse weight by defect, the researcher surveyed the questionnaires on the 103 engineers and the 31 experts on the landscape architectural construction. The result of this study are as follows. The relative importance by facilities pattern turn out to be much higher construction, material fator than design. environment factor in wood facilities, paving facilities, and steel facilities, the RIQMI is very high in timber crack, timber vending, faulty of timber against decay, welding faulty of steel facilities in material factor, and timber crack, faulty of timber against decay, finish faulty of steel facilities, welding faulty of steel facilities in construction factor.

• 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.

• 한국인터넷방송통신학회논문지
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• 제13권1호
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• pp.55-62
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• 2013

동판 생산량의 증가와 수요의 활성화로 더욱 동판에 대한 자동 검사 시스템이 필요하게 되었다. 본 연구에서는 동판의 3차원 표면형상 및 결함 검출을 하기 위한 3차원 영상 분석 시스템 및 GUI를 개발했다. 2차원 영상을 통해 분석을 할 수 있으나 오류가 많이 발생하기 쉽고, 작업자가 분석하기에는 무리가 따르기 때문에 3차원 영상으로 분석하여 살펴보고 자동으로 판정을 내리므로 작업자가 사용하기 쉽다. 동판 제작 공정에서 발생되는 검사 방법에서 사람에 의한 육안 검사가 주로 행해지고 있는데, 여기서 자동 검사를 통해 정확한 검사율과 비용 발생을 감소를 할 수 있다. 동판에 대한 결함을 정의하고, 동판 결함 검사 측정을 위한 시스템을 개발한다. 그리고 분석 알고리즘과 3차원 영상 분석 프로그램을 개발하여 동판에 결함을 자동 검출한다.

• 한국멀티미디어학회논문지
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• 제18권12호
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• pp.1519-1527
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• 2015

TFT-LCD automatic defect inspection system for detecting defects in place of the visual tester does pre-processing, candidate defect pixel detection, and recognition and classification through a blob analysis. An over-detection result of defects acts as an undue burden of blob analysis for recognition and classification. In this paper, we propose defect detection method based on the histogram distribution modeling of TFT-LCD image to minimize over-detection of candidate defective pixels. Primary defect candidate pixels are detected estimating the skewness of the luminance distribution histogram of the background pixels. Based on the detected defect pixels, the defective pixels other than noise pixels are detected using the distribution histogram model of the local area. Experimental results confirm that the proposed method shows an excellent defect detection result on the image containing the various types of defects and the reduction of the degree of over-detection as well.

• 한국산업정보학회논문지
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• 제19권6호
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• pp.43-51
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• 2014

TFT-LCD 영상은 다양한 특성의 결함을 포함하고 있다. 배경 영역과의 휘도 차이가 커서 육안으로 식별 가능한 결함부터 휘도 차이가 매우 적어서 육안 검출이 어려운 한도성 결함까지 포함한다. 본 논문에서는 휘도 차이를 이용하여 결함 영역에 포함될 확률이 높은 결함 화소부터 순차적으로 단계를 진행하면서 결함 후보 화소를 검출하고, 검출된 후보 화소를 블랍으로 구성하여 블랍의 크기와 주변 영역과의 휘도차이를 이용한 기법을 통해 최종적으로 결함 영역과 잡음을 구분하여 검출하는 알고리즘을 제안한다. 제안한 알고리즘의 타당성을 확인하기 위해 다양한 결함을 포함하는 영상에 대한 실험 결과를 살펴봄으로써 신뢰도 높은 결함 검출 결과를 입증하였다.

• 한국추진공학회지
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• 제16권2호
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• pp.65-72
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• 2012

초음파 결함 분석 프로그램은 초음파 반사법을 기반으로 초음파 신호처리 기법을 적용하여 개발되었고, FRP 층간분리 및 FRP/내열고무 미접착 결함을 정량적으로 측정할 수 있었다. 복합재 연소관에서 검출된 결함은 절단하여 전산화 단층촬영 및 영상 현미경으로 분석하였고, 결함 분석 프로그램의 결과와 일치하였다. 본 논문은 복합재 연소관의 초음파시험 데이터를 C-Scan 영상으로 변환하여 결함을 분석할 수 있는 프로그램 개발 과정을 기술하였다.