• 자동차안전학회지
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• 제7권4호
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• pp.20-25
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• 2015

The basic point of a vehicle recall is to remove vehicle defects as soon as possible and thus prevent possible road traffic accidents caused by the defects beforehand. Therefore, the core of vehicle recall under the self-certification system consists of a timely response and fast remedy of defects. The present study aimed to deduce a plan for improvement of the system necessary for the fast remedy of defects through a phased analysis of defect investigation procedure based on defect investigation statistical data. There will be a need to make the TSB(Technical Service Bulletin) or service campaign data submission of a manufacturer compulsory for the collection of broad defect information in the stage of information analysis and to impose a higher penalty when the manufacturer violates the data submission in the investigation stage. In addition, it is considered that an active service campaign should be induced and a punishment for late recall will be needed for consumer protection.

• 자동차안전학회지
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• 제7권4호
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• pp.31-38
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• 2015

In the United States, when NHTSA initiates the vehicle defect investigation, the most of automotive manufactures voluntary start their vehicle's recall campaign immediately. However, in the domestic market, NGOs, medias and even the National Assembly complaint the attitude of domestic and foreign makers tendencies of retardation of recall campaign. Also there were criticism for the manufacturer's concealing or downsize of their vehicle defects to the publics. In general, the manufactures may wait until MLIT's decision to recall orders. Therefore, in this study, from the survey of foreign countries legal recall systems and it is recommended reinforcement of the current vehicle management law to promote more frequent voluntary recall campaign from makers. In this study, it is also includes summarize all previous recall related research works and proposes the more stringent regulations to punish of concealing or downsize their vehicle safety defects.

• 산업경영시스템학회지
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• 제46권2호
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• pp.72-81
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• 2023

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

• 대한교통학회지
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• 제25권3호
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• pp.65-74
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• 2007

1995년 이후 연평균 6.2%의 증가율을 보이는 자동차 등록대수에 반해 연평균 교통사고 발생건수는 1.5%, 사망자 4.7% 및 부상자 0.3%씩 감소추세를 보이고 있어 매우 다행스러운 일이나, OECD국가와 비교해서는 여전히 높은 교통사고율을 보이는 것이 사실이다. 이에 정부 및 각 기관에서는 교통사고를 감소시키기 위해 지속적인 교통안전사업을 추진하고 있으나, 각 제도 및 사업에 대한 시행 효과를 측정하는 부분에 대해서는 소홀히 하고 있는 현실이다. 정부가 교통안전을 위한 사업의 일환으로 시행중인 자동차검사제도는 차량의 도로운행 적합성 확인을 통해 자동차의 안전도 확보 및 교통사고로 인한 국민의 생명과 재산을 보호하는 것을 목적으로 하고 있다. 하지만. 이 제도에 대한 효과분석이 제대로 이루어지지 않은 상황이고, 자동차검사제도와 무관하게 운전자 스스로 자동차의 안전관리 상태를 수시 점검한다는 의견 등 자동차 검사방법, 검사기준, 검사의 실효성 저하에 대한 논의가 지속적으로 제기되고 있는 실정이다. 이에 본 연구에서는 자동차검사제도가 구조장치의 안전성을 향상시키고. 자동차성능을 유지시킴으로써 자동차결함으로 인해 발생 가능한 교통사고의 사전예방에 어느 정도 기여하는지 정량적으로 보임으로써 자동차검사제도의 효과를 측정 해 보고자 하였다. 2005년도 자료를 기준으로 교통사고 감소건수를 추정해 본 결과 자동차검사제도 시행을 통한 교통사고 감소건수는 약 23,735건으로, 이는 2005년 총 교통사고 건수 214,171의 11%에 달하는 것으로 나타났다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 추계학술대회 논문집
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• pp.1097-1102
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• 2005

Non-Destructive Testing (NDT) is test method which finds the mechanical or natural or artificial defects of the interior or exterior of those without destructing materials and welded products. NDT is a means to assess the perfection of a component or system perfection. NOT images defects using scattered light, sound, electric current, magnetic fields and X-ray. Each NDT method has merits and demerits in the detecting ability of defects according to evaluated subjects. Defects can affect the serviceability of the material or structure, so NDT is important in guaranteeing safe operation as well as in quality control. In this review, we considered the methods of NDT applied to current railway vehicle manufacturing.

• 품질경영학회지
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• 제51권2호
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• pp.283-296
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• 2023

Purpose: The purpose of this study is to actually implement and verify whether welding defects can be detected in real time by utilizing deep learning AI solutions in the welding process of electric vehicle hairpin winding motors. Methods: AI's function and technological elements using synthetic neural network were applied to existing electric vehicle hairpin winding motor laser welding process by making special hardware for detecting electric vehicle hairpin motor laser welding defect. Results: As a result of the test applied to the welding process of the electric vehicle hairpin winding motor, it was confirmed that defects in the welding part were detected in real time. The accuracy of detection of welds was achieved at 0.99 based on mAP@95, and the accuracy of detection of defective parts was 1.18 based on FB-Score 1.5, which fell short of the target, so it will be supplemented by introducing additional lighting and camera settings and enhancement techniques in the future. Conclusion: This study is significant in that it improves the welding quality of hairpin winding motors of electric vehicles by applying domestic artificial intelligence solutions to laser welding operations of hairpin winding motors of electric vehicles. Defects of a manufacturing line can be corrected immediately through automatic welding inspection after laser welding of an electric vehicle hairpin winding motor, thus reducing waste throughput caused by welding failure in the final stage, reducing input costs and increasing product production.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권2호
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• pp.865-882
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• 2017

To improve passenger convenience and safety, today's vehicle is evolving into a "connected vehicle," which mounts various sensors, electronic control devices, and wired/wireless communication devices. However, as the number of connections to external networks via the various electronic devices of connected vehicles increases and the internal structures of vehicles become more complex, there is an increasing chance of encountering issues such as malfunctions due to various functional defects and hacking. Recalls and indemnifications due to such hacking or defects, which may occur as vehicles evolve into connected vehicles, are becoming a new risk for automakers, causing devastating financial losses. Therefore, automakers need to make voluntary efforts to comply with security ethics and strengthen their responsibilities. In this study, we investigated potential security issues that may occur under a connected vehicle environment (vehicle-to-vehicle, vehicle-to-infrastructure, and internal communication). Furthermore, we analyzed several case studies related to automaker's legal risks and responsibilities and identified the security requirements and necessary roles to be played by each player in the automobile development process (design, manufacturing, sales, and post-sales management) to enhance their responsibility, along with measures to manage their legal risks.

• 한국재난정보학회 논문집
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• 제17권1호
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• pp.112-119
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• 2021

연구목적: 본 연구는 일선 소방관서에 사용되고 있는 소방용 고가사다리차, 굴절사다리차, 화학차 및 펌프차의 최근 6년간의 정밀점검의 데이터를 기반으로 차종별로 시·도별 실시현황, 결함 발생률 및 연도별 결함 발생 사항 등을 파악하여 소방차량의 기술발전에 기여함을 목적으로 한다. 연구방법: 소방용의 고가사다리차, 굴절사다리차, 펌프차 및 화학차의 최근 6년간 정밀점검 기준에 따라 실시한 정밀점검 데이터를 통하여 차종별, 시·도별 실시현황 및 결함발생률, 연도별 결함사항을 분석하여 사용 연수에 따른 결함 발생 등의 현상을 분석하였다. 연구결과: 평균 230대 이상의 정밀점검 차량을 신청한 2012년에서 2017년도까지 시·도별 결과, 약간의 변동을 보여주기는 하지만 노후 소방차량 교체사업과 소방차량 제조업체의 대응 등으로 결함 발생 건수가 점차 감소 되는 결과를 보여주었다. 결론: 소방고가사다리차의 경우 결함발생율은 승강기장치, 전기장치, 사다리장치, 공압공급 장치의 순서로 결함의 발생률이 나타나는 것으로 파악되었으며, 소방굴절사다리차의 경우 굴절사다리, 유압실린더, 유압오일, 공압공급 장치의 순서로 결함의 발생률이 나타나는 것을 확인할 수 있었다. 소방화학차의 경우는 분말소화장치, 소방펌프, 진공펌프, 공압공급 장치의 부분에서 결함이 발생되는 것을 확인할 수 있었으며, 소방펌프차의 경우는 물탱크, 소방펌프, 진공펌프 및 공압공급 장치의 부분에서 결함이 발생하는 것을 확인할 수 있었다.

• 한국산학기술학회논문지
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• 제21권11호
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• pp.53-60
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• 2020

철도차량의 대차는 열차 주행을 위한 핵심적인 장치이다. 철도차량의 대차에서 피로결함은 운행 중 기대되지 않거나 과도한 하중, 용접결함, 재료 결함 등의 다양한 요인에 의해 발생할 수 있다. 철도차량의 사고를 방지하기 위해서 차체-대차연결부의 손상을 검출하고 발생 결함에 대한 정확한 평가가 요구된다. 이러한 철도차량의 차체-대차 연결부는 초음파 비파괴 검사를 통하여 건전성을 확보하고 있으나 결함 발생에 대한 학습기법을 이용한 판정방법이 필요하다. 최근 미세한 결함이나 유사한 결함을 높은 인식율로 검출하기 위하여 딥러닝 기법에 관한 여러 연구가 진행되고 있다. 본 연구에서는 철도차량의 차체-대차 연결부의 결함 검출능력을 위하여 용접부의 인공결함 시편에 대하여 데이터베이스 구축하였으며. 웨지형 초음파 센서를 이용하여 차체-대차 연결부에 대한 비파괴 검사를 수행하였다. 부가적으로 인적오류를 최소화하기 위하여 결함판단 학습기법인 합성곱 신경망기법(Convolutional Neural Network)을 적용하였다. 그 결과 합성곱 신경망기법 기법을 이용하여 철도차량의 차체-대차 연결 용접부의 균열을 99.98%이상 균열성 결함으로 판별할 수 있었으며 철도차량 차체-대차 연결부의 비파괴검사시 본 연구의 기술이 적용 가능함을 확인할 수 있었다.

• 대한안전경영과학회지
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• 제19권1호
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• pp.15-25
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• 2017

The findings were summarized as follows. The safety check by manufacturer showed that 6 of 13 companies are over the average occurrence of defects. It was expected that there would be a difference between manufacturing technology capability and production system of each manufacturer. Consequently, manufacturers should institutionally improve and strengthen certification items for the upward standardization of safety certification before factory. Second, the safety check by year showed that the results of this study accord with those of previous studies on defect time. Consequently, manufacturers should classify the 3-year-old equipment for vehicle-mounted MEWP into a special check subject to do a nondestructive test according to proven results, and also reflect the test in a safety test system to do regular preventive activities of equipment defects. Third, the safety check by part showed that the boom and outrigger parts of vehicle-mounted MEWP have the most defects. Stress concentration resulted in defects as the boom part was most frequently operated in the structural parts for a real work. To prevent this, it is suitable to improve the hardness of boom materials. The outrigger part needs improvement in safety devices with materials. As an outrigger supports the overturning moment of equipment, it is most affected by its load based on the operating radius, resulting in fatigue crack.