• Journal of Welding and Joining
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• v.32 no.4
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• pp.39-45
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• 2014

Today, the development of digitized information media and info-communications are bringing many changes. Due to the development of IT thechnology, we can learn wherever, whenever, regardless of time and place. Machine drawing subject is a very important in mechanical engineering course, but it's studyed only basic theory in a short period, average 1~2weeks. So that, students think that the mechanical drawing is of minor importance. Such ideas make them difficult to impove sense of space in isometric drawing and drawing skill. Therefore, in this paper, augmented reality-based contents through the system, Mechanical Drawing of education to meet the effectiveness and satisfaction, student learning can be spontaneously it was construct self-system. And, Theoretical part of the Mechanical Drawing is proposed ensure more efficient and easier training. In this paper, we were test operation for user effectualness of proposed service at Korea Polytechnics Colleges a industrial facilities management in Daegu. Target user are 66 students, and The students were divided into experimental group and comparison group. Experimental results, experimental group was able to do systematically experience many Projection Drawing and Pictorial Drawing in short schooltime. And, The test operation results showed that have the possibility to meet education effectiveness and user satisfaction in this augmented reality-based contents system.

• Journal of Ocean Engineering and Technology
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• v.27 no.3
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• pp.79-84
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• 2013

The seawater pipes in the engine rooms of ships are surrounded by severely corrosive environments caused by fast flowing seawater containing chloride ions, high conductivity, etc. Therefore, it has been reported that seawater leakage often occurs at a seawater pipe because of local corrosion. In addition, the leakage area is usually welded using shielded metal arc welding with various electrodes. In this study, when seawater pipes were welded with four types of electrodes(E4311, E4301, E4313, and E4316), the difference between the corrosion resistance values in their welding zones was investigated using an electrochemical method. Although the corrosion potential of a weld metal zone welded with the E4316 electrode showed the lowest value compared to the other electrodes, its corrosion resistance exhibited the best value compared to the other electrodes. In addition, a heat affected zone welded with the E4316 electrode also appeared to have the best corrosion resistance among the electrodes. Furthermore, the corrosion resistance of the weld metal zone and heat affected zone exhibited relatively better properties than that of the base metal zone in all of the cases welded with the four types of electrodes. Furthermore, the hardness values of all the weld metal zones were higher than the base metal zone.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.393-406
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• 1993

In resistance spot welding process, size of molten nuggest have been utilized to assess the integrity of the weld quality. However real-time monitoring of the nugget size is an extremely difficult problem. This paper describes the design of an artificial neural networks(ANN) estimator to predict the nugget size for on-line use of weld quality monitoring. The main task of the ANN estimator is to realize the mapping characteristics from the sampled dynamic resistance signal to the actual negget size through training. The structure of the ANN estimator including the number of hidden layers and nodes in a layer is determined by an estimation error analysis. A series of welding experiments are performed to assess the performance of the ANN estimator. The results are quite promissing in that real-time estimation of the invisible nugget size can be achieved by analyzing the dynamic resistance signal without any conventional destructive testing of welds.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.1
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• pp.27-33
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• 1997

A neural network approach has been developed to determine the depth of a surface breaking crack in a steel plate from ultrasonic backscattering data. The network is trained by the use of feedforward three-layered network together with a back-scattering algorithm for error correction. The signal used for crack insonification is a mode converted 70$^{\circ}$transverse wave. A numerical analysis of back scattered field is carried out based on elastic wave theory, by the use of the boundary element method. The numerical data are calibrated by comparison with experimental data. The numerical analysis provides synthetic data for the training of the network. The training data have been calculated for cracks with specified increments of the crack depth. The performance of the network has been tested on other synthetic data and experimental data which are different from the training data.

• Journal of Welding and Joining
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• v.11 no.2
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• pp.27-41
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• 1993

The estimation of nugget sizes was attempted by utilizing the artificial neural networks method. Artificial neural networks is a highly simplified model of the biological nervous system. Artificial neural networks is composed of a large number of elemental processors connected like biological neurons. Although the elemental processors have only simple computation functions, because they are connected massively, they can describe any complex functional relationship between an input-output pair in an autonomous manner. The electrode head movement signal, which is a good indicator of corresponding nugget size was determined by measuring the each test specimen. The sampled electrode movement data and the corresponding nugget sizes were fed into the artificial neural networks as input-output pairs to train the networks. In the training phase for the networks, the artificial neural networks constructs a fuctional relationship between the input-output pairs autonomusly by adjusting the set of weights. In the production(estimation) phase when new inputs are sampled and presented, the artificial neural networks produces appropriate outputs(the estimates of the nugget size) based upon the transfer characteristics learned during the training mode. Experimental verification of the proposed estimation method using artificial neural networks was done by actual destructive testing of welds. The predicted result by the artifficial neural networks were found to be in a good agreement with the actual nugget size. The results are quite promising in that the real-time estimation of the invisible nugget size can be achieved by analyzing the process variable without any conventional destructive testing of welds.

• Proceedings of the KWS Conference
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• 2010.05a
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• pp.49-49
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• 2010

용접은 산업계의 기계 조립 및 접합을 위한 공정의 주요한 작업으로 조선, 중공업, 건설 등 산업현장에서 사람에 의한 수동적인 작업으로 대부분 수행된다. 이러한 용접 작업을 수행하는 용접 기술자는 산업 현장 훈련원과 직업 교육 학교에서 양성되지만 용접 훈련 과정은 실습 초보자에게 위험하고, 장시간 교육하기에 어려울 뿐 아니라 재료 낭비, 의사 소통의 한계, 즉석 결과 평가의 한계, 공간부족 등 다양한 문제가 있다. 그러므로, 안전하고 반복적인 실습 환경 제공하고 장시간 및 다수 교육참여 지원 등이 가능한 시스템을 구축하여 숙련된 우수 인력 조기 확보와 훈련 비용을 절감할 필요가 있다. 본 논문에서는 실제와 동일한 상호작용을 제공할 뿐만 아니라 고품질로 훈련 환경을 가시화하여 용접 상황을 동일하게 모사하는 가상 현실 기반 용접 훈련 시뮬레이터를 제시한다. 이 시스템은 용접의 형상과 환경의 고품질 가시화, 경험 DB를 통한 용접의 비드 형상 데이터 획득, 용접 토치를 이용하는 사용자 상호작용, 용접 훈련 결과 평가 및 최적 작업 가이드, 용접 콘텐츠 저작, 다양한 용접 훈련을 가시화하는 하드웨어 플랫폼으로 구성된다. 고품질 가상 용접 가시화는 경험 DB 기반 비드 형상 데이터와 신경회로망을 이용한 비드 형상 예측을 통해 실시간 비드 표현이 이루어지며 쉐이더 기반 고품질 모재 및 비드 표현, 아크 불꽃 효과 표현을 포함한다. 사용자 상호작용은 현장 작업 도구와 일치된 토치 인터페이스와 위치추적을 이용하여 토치의 작업각, 진행각, 속도, 거리 등을 반영할 수 있으며 진동과 소리 등 용접 훈련의 사실적 상호작용도 재현하였다. 용접 훈련 평가 및 최적 작업 가이드는 훈련자의 용접속도, 거리, 각도 등의 사용자 작업 결과를 그래픽으로 표현하고, 애니메이션을 통한 훈련 자세를 추후 분석할 수 있도록 하였고, 가상토치, 기준선, 수치계기 등을 이용한 최적 작업 훈련 가이드 제시하였다. 훈련 콘텐츠 저작은 메뉴UI 기반으로 용접의 전류, 전압 등의 조건과 상황을 선택하도록 제시하였고, 하드웨어 플랫폼은 워크벤치형 입체 디스플레이 방식으로 용접 환경을 가시화하였고, 위, 정면, 아래보기 등 다양한 용접 자세 변경을 지원 할 수 있도록 구축하였다. 이러한 가상현실 기반 훈련 시뮬레이터는 아크열 발생에 따른 장시간 훈련의 어려움을 극복할 수 있고, 다양한 실습 환경을 바꾸어 가며 반복적인 훈련이 가능하고, 실 재료를 사용하지 않아 재료의 낭비를 줄일 수 있는 환경 친화적인 안전하고 효율적인 훈련 실습 환경을 제공할 수 있다.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.71-82
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• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.53-62
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• 2023

This paper has suggested the necessity of introducing training contents using XR(Extended reality) technology as a way to lower the high rate of nursing accidents among unskilled technical personnel in domestic shipbuilding industry, focusing on cable pulling using winch. The occurrence rate of nursing accidents in the domestic shipbuilding industry was almost double(197.4%) (2017~2020) when compared with other manufacturing industries. In particular, it is worth noting that more than 31.8% of nursing accidents in the shipbuilding industry occurred among workers whose job experience is no more than 6 months. Most of new workers are seen to have hard time due to several factors such as lack of work information, inexperience, and unfamiliarity with the working environments. This indicates that it is essential to incorporate more effective training method that could help new workers become familiar with technical skills as well as working environments in a short period of time. Currently, education/training at the domestic shipyard is biased toward technical skills such as welding, painting, machine installation, and electrical installation. Contrary, even more important training required to get new workers used to the working environment has remained at a superficial level such as explaining ship building processes using 2D drawings. This may be the reason why it is inevitable to repeat similar training at OJT (On-the-Job Training) even at the leading domestic companies. Domestic shipbuilding industries have been attracting a lot of new workers thanks to recent economic recovery, which is very likely to increase the occurrence of disasters. In this paper, the introduction of training using XR technology was proposed, and as a specific example, the process of pulling cables using winches on ships was implemented as XR-based training content by using Unity. Using the developed content, it demonstrated that new workers can experience the actual work process in advance through simulation in a virtual space, thereby becoming more effective training content that can help new workers become familiar with the work environment.

• Journal of the Korean Society of Safety
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• v.38 no.3
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• pp.77-84
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• 2023

Welding and cutting, which are representative tasks in handling firearms at industrial sites, are the basis for production and maintenance processes across all industries. They are also essential in the root industry. Specifically, they are widely used in the manufacturing industry, including equipment industries such as shipbuilding, automobiles, and chemicals, and subsequent maintenance work and general facility repair. However, such hot work carries a high fire risk owing to sparks scattering and inadequate management, resulting in a high occurrence of accidents. In response, the government and relevant organizations have recently revised the Occupational Safety and Health Act to prevent accidents during hot work. These revisions impose more stringent regulations than before, which are expected to help prevent actual fire accidents. However, whether the fire observer system, which is the core element of the revision, would be practically applied and maintained is unclear. Therefore, this study compared the fire observer system in the revised Occupational Safety and Health Act with those in the laws and systems of developed countries, conducted interviews with safety and health experts to assess the suitability of the new system for fire observer operations, and improvement plans were derived accordingly. Therefore, the laws and systems of developed countries grant more authority to fire observers compared with those of Korea. Moreover, professional training in handling emergency is required. Interviews with safety and health experts revealed that regardless of company size, the same operating standards were applied, and standards for deploying fire observers in various locations were unclear. Furthermore, there was a lack of professional education and training, and the role and authority of fire observers were limited. These findings revealed a problem in this sector. The results of this study are expected to serve as basic data for establishing a practical system for placing fire observers and supplementing laws, guidelines, and systems for preventing fire accidents.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.775-785
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• 2022

By analyzing the operation status of fire safety management of small construction site workers, deriving problems, and suggesting improvement measures, this study was conducted to present practical basic data for their efficient use in the future, and the following conclusions were drawn. First, it was analyzed that small construction site workers are elderly in the age group of construction workers, have short construction skills, most of the jobs are working in the construction industry, and the employment type is non-regular workers. Second, the fire safety management improvement plan of small construction site workers is systematized, fire safety manager is deployed to manage fire risk, fire escape routes and emergency warning facilities are provided to inform all workers at the construction site. In addition, measures to reduce industrial accidents are needed through realistic evacuation training, fire VR training, and interesting educational programs.