• Korean Journal of Construction Engineering and Management
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• v.10 no.5
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• pp.16-27
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• 2009

Recently construction companies expand position for apartment house in construction market because of house supply rate increase and its amount. In addition, because the focus of house sale market has moved to customer from supplier, the importance of defect management is being issued currently. However, current apartment defect management is not satisfied with customer's demand for the lack of business process management, management organization, information feedback, and readiness for defect in construction phase. To solve this problem, this study proposed business process management improvement model for defect management. Proposed improvement model make information feedback, defect management business quality improvement, and improper process improvement through integrating defect management and quality management. It is expected to contribute to customer's satisfaction improvement and reliance improvement for construction companies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.369-377
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• 2023

In the industrial manufacturing sector, quality control is pivotal for minimizing defect rates; inadequate management can result in additional costs and production delays. This study underscores the significance of detecting texture defects in manufactured goods and proposes a more precise defect detection technique. While the DFR(Deep Feature Reconstruction) model adopted an approach based on feature map amalgamation and reconstruction, it had inherent limitations. Consequently, we incorporated a new loss function using statistical methodologies, integrated a skip connection structure, and conducted parameter tuning to overcome constraints. When this enhanced model was applied to the texture category of the MVTec-AD dataset, it recorded a 2.3% higher Defect Segmentation AUC compared to previous methods, and the overall defect detection performance was improved. These findings attest to the significant contribution of the proposed method in defect detection through the reconstruction of feature map combinations.

• Laser Solutions
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• v.15 no.1
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• pp.6-9
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• 2012

In TFT-LCD manufacturing process, various defects are generated by manufacturing machine trouble or particle. These defects can be repaired through the TFT-Laser repair process that only can't be automated in TFT-LCD manufacturing Process. In this Paper, we propose auto defect algorithm for TFT-LCD laser repair machine using image processing algorithm in order to automate process. Proposed algorithm can detect very small defects (< 2um) in 98% success ratio, and generated laser repair path guarantee highly precise position accuracy. Through proposed system, much of the work still done the old-fashioned way, by hand, can be automated and manufacturing company can be strengthed the competitiveness of cost.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.578-595
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• 2020

Submarine pressure hulls must withstand high hydraulic pressure and be free of defects. To improve the precision of defect detection, we herein examined different probes for optimal defect assessment by applying the Phased Array Ultrasonic Testing (PAUT) method. Two sets of probe design parameters were selected by considering pressure hull characteristics and analyzed through modeling. PAUT probes were applied, and defect assessment results were compared based on ultrasonic signals of various simulated defects in specimens designed to be the same as actual pressure hulls. The final selected design parameters for the submarine probe, which were designed to minimize the grating lobe of wave interference effect and improve the ultrasonic resolution of pressure hull welds, were identified through the experiment. The improvement in the probe's ability to detect defects in a pressure hull was verified. Furthermore, the accuracy of defect length measurement was improved, enhancing the applicability of the technique.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.627-628
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• 2015

Construction defect which can causes economic damage such as schedule delay, cost overrun is a considerably important factor in construction industry. In general, a construction defect features a difficulty to find out causes precisely because it occurs when several interrelated causes combine. Yet, studies have tried to understand the interrelationships between factors are limited. In addition, despite of a tremendous amount of construction data, it's not still enough to analyze them, but tends to depend on experience or know-how of practitioners. Thus, it is necessary to identify underlying causes in influential factors by utilizing related data. This paper analyses Interrelationships between causal factors using Association Rule Mining to discover root causes of construction defects. Confidence and Lift that can be used for presenting the interrelationships of the causes were extracted from 1241 cases in 30 projects in Korea. It is expected that this paper allows the construction managers to discover key factors and make right decisions to reduce occurrence of construction defects. Furthermore, analysis of interrelationships can improve understanding of structural patterns of construction defects.

• Korean Journal of Materials Research
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• v.32 no.9
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• pp.396-402
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• 2022

In this study, surface roughness and interfacial defect characteristics were analyzed after forming a high-k oxide film on the surface of a prime wafer and a test wafer, to study the possibility of improving the quality of the test wafer. As a result of checking the roughness, the deviation in the test after raising the oxide film was 0.1 nm, which was twice as large as that of the Prime. As a result of current-voltage analysis, Prime after PMA was 1.07 × 10 A/cm² and Test was 5.61 × 10 A/cm², which was about 5 times lower than Prime. As a result of analyzing the defects inside the oxide film using the capacitance-voltage characteristic, before PMA Prime showed a higher electrical defect of 0.85 × 10¹² cm^-2 in slow state density and 0.41 × 10¹³ cm^-2 in fixed oxide charge. However, after PMA, it was confirmed that Prime had a lower defect of 4.79 × 10¹¹ cm^-2 in slow state density and 1.33 × 10¹² cm^-2 in fixed oxide charge. The above results confirm the difference in surface roughness and defects between the Test and Prime wafer.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.273-274
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.255-256
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.359-360
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.813-814
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• 2012