• Journal of the Korea Institute of Building Construction
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• v.13 no.4
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• pp.341-350
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• 2013

For this study, a series of interviews with engineers in the Korean construction industry was carried out through a formal workshop format to analyze the causes of the inferior quality of builders' hardware. The authors established the causes of defects in window hardware construction in relation to the three aspects of system, design, and construction as involving the following seven factors: lack of system (including low ability to create construction specifications); low social awareness of the importance of window hardware; low technical capability to create design drawings; low design costs; small manufacturing capacity; low construction cost; and short duration of construction. Among the seven causes, the biggest cause of defects in window hardware construction is the lack of a system (low ability to create construction specifications), followed by low technical capability to create design drawings. In addition, this study carried out basic research to create measures to prevent defects in window hardware construction by analyzing how such causes of defects are distributed depending on the scale of architectural firms and construction companies during actual projects.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.4
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• pp.686-692
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• 2013

Today, environmental issues have become a matter of worldwide concern. In particular, automobile industries engage in considerable research and investment to develop high-efficiency and ecofriendly cars. Most ecofriendly cars use natural gas or hydrogen gas instead of fossil fuels. In this regard, low-weight and high-pressure vessels have gradually been developed to increase the driving distance of a car. However, most pressure vessels installed in cars develop many defects over time owing to shocks sustained when the car is being driven. Such defects can cause the explosion of the pressure vessel. Therefore it is important to prevent such explosions due to internal defects. The use of shearography for measuring the internal defects of objects afford many advantages. It is a non-contact and non-destructive method, and it is not limited by the object shape. In this study, the internal defect deformation and strain of an aluminum liner that is used in a CNG bus for the fuel storage tank is measured using shearography. It is important to measure the strain and deformation in order to detect defects and repair the pressure vessel. To verify the accuracy of the shearography measurement method, the measurement results of shearography, out-of-plane ESPI, and FEM are compared quantitatively.

• Archives of Craniofacial Surgery
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• v.19 no.4
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• pp.260-263
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• 2018

Background: The alar and nasal tip are important subunits of the nose. Determining the optimal procedure for reconstructing a cutaneous defect in a nasal subunit depends on several factors including size, location, and involvement of deep underlying structures. We treated cutaneous defects after tumor ablation in the alar and nasal tip with a local flap, using an S-shaped design and a modified V-Y advancement flap with a croissant shape. Methods: We analyzed 36 patients with skin tumors who underwent flap coverage after tumor ablation. Rotation flaps were used in 26 cases and croissant-shaped V-Y advancement flaps were used in 10 cases. The primary cause of the defects was skin cancer, except for one benign tumor. Results: The mean patient age was 71 years. The size of the defects ranged from $0.49cm^2$ to $3.5cm^2$. No recurrence of skin cancer was noted and all flaps lasted until the end of follow-up. Partial desquamation of the epidermis was noted in one case. The postoperative appearance for most patients was excellent, objectively and subjectively. Conclusion: For cutaneous defects of up to about $4.0cm^2$ of the alar and nasal tip, local flaps using our methods offered a good cosmetic and therapeutic result. The main advantage of our flaps is the minimal dissection required compared to bilobed and other local flap methods. We believe our flaps are a suitable option for alar and nasal tip reconstruction.

• Archives of Plastic Surgery
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• v.50 no.3
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• pp.233-239
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• 2023

Background Trunk defects can occur because of surgical site infections after spinal surgery, resection of malignant tumors, or trauma. Herein, we present our experience of using intercostal artery perforator (ICAP) flaps to reconstruct trunk defects without noteworthy complications. Fourteen patients underwent reconstruction with ICAP flaps between March 2015 and March 2019. Methods Patients' data, including age, sex, the cause of the defect, defect size, perforator location, flap size, complications, and follow-up period, were retrospectively reviewed. The mean age of the patients was 56.5 years (range, 19-80 years). All operations were performed after the results of bacterial culture from the wound showed no microbial growth. We found reliable perforators around the defect using Doppler ultrasonography. The perforator flaps were elevated with a pulsatile perforator and rotated in a propeller fashion to the defects. We performed five dorsal and two lateral ICAP flaps. The mean flap dimensions were 12 × 5.5 cm² (range, 6 × 5 to 18 × 8 cm²). Results Primary closure of the donor site was performed. Marginal congestion was observed as a complication in one case, but it healed with no need for revision. The mean follow-up period was 8 months. All patients were satisfied with the surgical outcomes. Conclusion ICAP flaps can be easily mobilized, thereby reducing donor site morbidity without sacrificing the underlying muscles for trunk reconstruction. Therefore, these flaps are useful options for the reconstruction of trunk defects.

• Journal of the Korea Institute of Building Construction
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• v.11 no.5
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• pp.459-467
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• 2011

The work of constructing apartment housing involves various fields of industry that are linked to each other, and is based on a design document prepared by multiple technicians and architects. Consequently, design errors, material flaws or faulty construction works can cause defects, which sometimes overlap with each other. Construction companies should repair any defects found in a completed building within a specified period of time, and to do this, should establish a business plan by efficiently predicting the cost of defect repair. As it is very difficult for companies to accurately predict the occurrence of defects, historical performance data is used as a base. For domestic apartment housing units, data on the cost of defect repair is insufficient, so there are hardly any methods that can be used to make precise predictions. Therefore, the intent of this study is to develop a model that can predict the cost of defect repair by supply type and area, based on historical performance data with ten years worth of post-completion.

• Journal of Magnetics
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• v.16 no.1
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• pp.36-41
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• 2011

If gas is leaking out of gas pipelines, it could cause a huge explosion. Accordingly, it is important to ensure the integrity of gas pipelines. Traditionally, over the years, gas-operating companies have used the ILI system, which is based on axial magnetic flux leakage (MFL), to inspect the gas pipelines. Relatively, there is a low probability of detection (POD) for the axial defects with the axial MFL-based ILI. To prevent the buried pipeline from corrosion, it requires a protective coating. In addition to the potential damage to the coating by environmental factors and external forces, there could be defects on the damaged coating area. Thus, it is essential that nondestructive evaluation methods for detecting axial defects (axial cracks, axial groove) and damaged coating be developed. In this study, an electromagnetic acoustic transducer (EMAT) sensor was designed and fabricated for detecting axial defects and coating disbondment. In order to validate the performances of the developed EMAT sensor, experiments were performed with specimens from axial cracks, axial grooves, and coating disbondment. The experimental results showed that the developed EMAT sensor could detect not only the axial cracks (minimum 5% depth of wall thickness) and axial grooves (minimum 10% depth of wall thickness), but also the coating disbondment.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.555-561
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• 2000

The remote field eddy current (RFEC) inspection was performed on the ductile cast iron pipes with nominal outer diameter of 100mm, which were machined with various shapes and sizes of defects. Ductile cast iron pipes which are used as water supply pipe have the non-uniform thickness and asymmetric cross section due to relatively high degree of allowable errors during the manufacturing processes. These characteristics of ductile cast in pipes cause the long range background noises in RFEC signals along the pipe. In this study, tile machined defects in pipes were effectively classified by the moving window average (MWA) method which eliminated the long-range noise. The voltage plane polar plots (VPPP) method was used to quantitatively evaluate the depth and circumferential degree of defects. The VPPP signatures showed that the angle between defect signature and the normalized in-phase component on the VPPP is linear to the depth of defects. The nondestructive RFEC technique proved to be capable of quantitatively evaluating the machined defects of underground water supply pipe.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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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.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.407-416
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• 2009

To support an efficient management of software verification and validation activities, much research has been conducted to predict defects in early phase. And defect prediction models have been proposed to predict defects. But the generality of the models has not been experimentally studied for other software system. In other words, most of prediction models were applied only to the same system that had been used to build the prediction models themselves. Therefore, we performed an experiment to explore generality of major prediction models. In the experiment, we applied three defects prediction models to three different systems. As a result, we cannot find their generality of defect prediction capability. The cause is analyzed to result from a different metric distribution between the systems.

• Journal of the Korean Institute of Gas
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• v.11 no.2 s.35
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• pp.60-64
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• 2007

Chemical Process industry in Korea has over 30 year's of history and is likely to face potential incidents. The traditional risk analysis and control system in Chemical Process industry focuses on mechanical defects, overlooking the human performance control. Although development of automation technology and controlling technology was necessary, human decision factor is essential to preventing accidents in the Chemical Process. Almost all serious accidents take place when inappropriate humanperformance and mechanical defects of safety equipments simultaneously occurs. The AHRA(Advanced Human Reliability Analyzer) software has been developed to collect failure data and analyze human error probability (Reliability) in Chemical Process Industry in Korea. This paper describes the HRA analysis result of PIF(Performance Influencing Factor) evaluation, HEP(Human Error Probability) and root cause of accidents by applying a Chemical Process Industry related accident data. This analysis result should present a scheme that, by controlling human error factor other than putting safety management funds into the machinery in plants, can reduce cost and maximize the safety in Chemical Process Industry.