• 산업경영시스템학회지
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• 제46권2호
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• pp.1-12
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• 2023

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.

• 반도체디스플레이기술학회지
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• 제20권1호
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• pp.99-103
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• 2021

Warpage defect detecting of scaffold is very important in biosensor production. Because warpaged scaffold cause problem in cell culture. Currently, there is no detection equipment to warpaged scaffold. In this paper, we produced detection model for shape warpage detection using deep learning based CNN. We confirmed the shape of the scaffold that is widely used in cell culture. We produced scaffold specimens, which are widely used in biosensor fabrications. Then, the scaffold specimens were photographed to collect image data necessary for model manufacturing. We produced the detecting model of scaffold warpage defect using Densenet among CNN models. We evaluated the accuracy of the defect detection model with mAP, which evaluates the detection accuracy of deep learning. As a result of model evaluating, it was confirmed that the defect detection accuracy of the scaffold was more than 95%.

• Clinics in Shoulder and Elbow
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• 제7권2호
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• pp.70-75
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• 2004

Purpose: To evaluate the results of arthroscopic repair of traumatic anterior shoulder instability with glenoid bone defect. Materials and Methods: Nineteen patients who had underwent arthroscopic repair for the shoulder with traumatic anterior instability and glenoid bone defect were retrospectively reviewed. Mean age was 24.6 years(range, 20 to 39) and mean follow-up was 23 months(range, 19 to 55). No glenoid bone defect was greater than 7mm in length and 20% of the glenoid. The results were evaluated according to stability, range of motion and function. Results: All patients obtained excellent-good results according to Rowe scoring system. Two patients(10.5%) had instability. The mean loss of external rotation was 15 degrees (range, 0 to 25). Functionally, 17 patients could participate in preinjured work or sports to the same level with or without mild discomfort. The remained 2 patients who had 25 degree loss of external rotation could not play sports. Conclusion: Though arthroscopic repair is a good treatment for traumatic anterior shoulder instability with small glenoid bone defect, it is possible to cause loss of external rotation

• 한국화재소방학회논문지
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• 제30권3호
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• pp.94-103
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• 2016

이 논문에서는 1년 전에 구입하여 8,500 km를 주행한 차량에서 발생한 화재사례를 분석하였다. 이 차량은 차량이 적색교통신호로 멈추었다가 파란불로 바뀌어 출발할 때 옆 차량이 경음기를 울려서 차량을 세워 확인해보니 엔진 쪽에 불이 붙어 있었다. 이 차량 화재는 배터리 + 단자에 삽입하여 나사로 조이는 고리의 전기적인 스파크로 인해 발생하였을 가능성이 높은 것으로 분석하였다. 그리고 그 고리의 전기적인 스파크는 제조결함으로 인해 발생한 것이므로 화재발생책임은 소유자나 운전자와 관련이 없이 제조자에게 있는 것으로 분석하였다. 이 차량화재의 화재발생책임과 관련하여 법원에서 제조자의 제조결함을 인정하였다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2008년도 추계 학술논문 발표대회
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• pp.181-186
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• 2008

The purpose of this study is analyzing the frequent defect about each inspection part of Pre-qualification of residential building reconstruction and finding the cause of occurrence so that can supply a solution of the problem during the plalnning and constructure. The frequent defects are naturally following the deterioration and more occur in the structure body than a skin. The meaning that supply the cause and the managing method for preventing frequent defects about each inspection part is as follows. To prevent the defects, it is needed that the choice of the appropriate materials, giving a sufficient space for facilities, reliable constructure for the part of expecting the defects. The quality of life will go up due to making a good dwelling environment and extending the life cycle of structures from the inspection and managing the part of expecting defects.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.101.6-101
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the product(bad pallets). An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labeling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets ...

• Archives of Reconstructive Microsurgery
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• 제17권2호
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• pp.82-86
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• 2008

Purpose: Soft tissue defect can occur on the posterior aspect of the elbow after trauma or fracture fixation. To cover the defect and maintain elbow functions, various flap surgeries including latissimus dorsi muscle flap, lateral arm flap and radial forearm flap can be performed. We present the clinical results of transposition lateral arm flap for coverage of the elbow defect and discuss the cause of posterior soft tissue necrosis after fracture fixation. Materials and Methods: Two patients who had posterior soft tissue defect of the elbow after open reduction of the fractures around the elbow were treated with transposition lateral arm flap. The mean size of skin defect was 20 $cm^2$. The flap was elevated with posterior radial collateral artery pedicle and transposed to the defect area. Donor defect was covered with split thickness skin graft. The elbow was immobilized for 1 week in extended position and active range of motion was permitted. Results: All two cases of transposition lateral arm flap survived without marginal necrosis. The average range of motion of the elbow was 10~115 degrees. Mayo elbow performance score was 72 and Korean DASH score was 23. Conclusion: When elbow fractures are fixed with three simultaneous plates and screws, skin necrosis can occur on the posterior aspect of the elbow around olecranon area. If the size of skin defect is relatively small, transposition lateral arm flap is very useful option for orthopaedic surgeons without microsurgical technique.

• Journal of Korean Neurosurgical Society
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• 제42권2호
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• pp.89-91
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• 2007

Objective : Cranioplasty is necessary to repair the cranial defect, produced either by decompressive craniectomy or removal of the contaminated depressed skull fracture. Complications are relatively common after cranioplasty, being reported up to 23.6%. We examined the incidence and risk factors of infectious complications after cranioplasty during last 6 year period. Methods : From January 2000 to December 2005, 107 cranioplasties were performed in our institution. The infectious complications occurred in 17 cases that required the removal of the bone flap. We examined the age of the patients, causes of the skull defect, timing of the cranioplasty the size of the defect, and kinds of the cranioplasty material. The size of the skull defect was calculated by a formula, $3.14{\times}long\;axis\;{\times}short$ axis. The cranioplasty material was autogenous bone kept in a freezer in 74 patients, and polymethylmetacrylate in 33 patients. Statistical significance was tested using the chi-square test. Results : The infection occurred in 17 patients in 107 cranioplasties (15.9%). It occurred in 2 of 29 cases of less than $75\;cm^2$ defect (6.9%), and 6 in 54 cases of $75{\sim}125\;cm^2$ defect (11.1%). Also, it occurred in 9 of 24 cases of more than $125\;cm^2$ defect (37.5%). This difference was statistically significant (p <0.01). Conclusion : During the cranioplasty, special attention is required when the skull defect is large since the infection tends to occurr more commonly.

• 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.

• Journal of Preventive Medicine and Public Health
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• 제14권1호
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• pp.13-22
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• 1981

A study was conducted to provide comprehensive information on epidemiological state of crippled schoolchildren in Chungnam area from November 23,1979 to June 19,1980. In this study, two step survey was conducted upon whole primary, middle and high school, and subsequent selected 537 cases in total 3,063 crippled children. The results obstained are as follows; 1. The prevalence rate of orthopedic defect children was 3.7 per 1,000 and dominant male as 6:4. 2. It was relatively higher the school grade and prevalence rate more increased. Prevalence rate was highest in high school as 4.7 per 1,000, middle in middle school as 4.4 per 1,000 and lowest in primary school as 3.1 per 1,000. 3. The most predominant group was $15{\sim}19$ age as 52.9 percent. 4. The most common job of their parent was agriculture as 52.9 percent and next job sales and service. Economic state of Cripple's parent have revealed no particular difference. 5. In a family, the most common incidence rate was first children in both sex and decreased by ordered sibling. 6. Poliomyelitis was the most common cause as 71.5 percent and next cerebral palsy 11.9 percent. 7. The most common affected site was lower extremity (Right: 42.3%, Left: 35.5%) and next upper extremity. Right was more dominant as 55 : 45. 8. Intelligence was decresed in cerebral palsy predominantly than other cause of defect, including poliomyelitis. 9. For the treatment of their condition at onset of illness, crippled children was utilized private clinic and herb medicine, but was changed tendency of treatment as acupucture and moxibustion after diagnosis of cause of defect.