• Journal of Auto-vehicle Safety Association
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• v.7 no.4
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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.

• Journal of Auto-vehicle Safety Association
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• v.7 no.4
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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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.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.65-74
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• 2007

Vehicle inspection is a system to help all vehicles function safely through periodic maintenance. Vehicle inspections have been performed since 1962 in Korea by the government in order to reduce traffic accidents due to vehicle defects. Also, vehicle inspections may help protect citizens against uninsured vehicles and illegal vehicle remodeling by discovering and disclosing those vehicles. The prime objective of vehicle inspection is to guarantee all vehicles drive safely on the road by inspecting and fixing items which can affect traffic accidents. In addition, vehicle inspections may help to improve the public order related to vehicle operations and prevent crime through the confirmation of vehicle identity and authentication of ownership. Although there are many benefits of vehicle inspection. there are some negative opinions of the system. In this study, a methodology to analyze the effectiveness of the vehicle inspection system quantitatively in terms of traffic safety was developed. According to the developed methodology. accidents were reduced by 23.735, which is 11% of the total number of accidents in 2005.

• Proceedings of the KSR Conference
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• 2005.11a
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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.

• Journal of Korean Society for Quality Management
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• v.51 no.2
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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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• v.11 no.2
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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.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.112-119
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• 2021

Purpose: This study is based on the detailed inspection data for the last 6 years of fire-fighting high ladder vehicles, fire-fighting inflected ladder vehicles, fire-fighting chemical vehicles and fire-fighting pump vehicles used in front-line fire departments. The purpose is to contribute to the technological development of fire-fighting vehicles by grasping the implementation status of each city and province, the rate of defects, and the occurrence of defects by year. Method: The implementation status by city and province, defect incidence rate, and defect occurrences by year were analyzed. Result: From 2012 to 2017, when the average of 230 or more overhaul vehicles was requested, the results of each city/province show slight fluctuations, but the number of defects gradually decreased due to the old fire-fighting vehicle replacement project and the response of fire vehicle manufacturers. Conclusion: In the case of fire-fighting ladders, the incidence rate of defects was found to be in the order of elevator device, electric device, ladder device, and pneumatic supply device. And in the case of the fire fighting ladder, it was confirmed that the incidence of defects appeared in the order of the refractive ladder, hydraulic cylinder, hydraulic oil, and pneumatic supply device. In the case of fire-fighting chemical vehicles, it was confirmed that defects occurred in the powder fire extinguishing device, fire pump, vacuum pump, and pneumatic supply device.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.53-60
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• 2020

The bogies of railway vehicles are one of the most critical components for service. Fatigue defects in the bogie can be initiated for various reasons, such as material imperfection, welding defects, and unpredictable and excessive overloads during operation. To prevent the derailment of a railway vehicle, it is necessary to evaluate and detect the defect of a connection weldment between the car body and bogie accurately. The safety of the bogie weldment was checked using an ultrasonic test, and it is necessary to determine the occurrence of defects using a learning method. Recently, studies on deep learning have been performed to identify defects with a high recognition rate with respect to a fine and similar defect. In this paper, the databases of weldment specimens with artificial defects were constructed to detect the defect of a bogie weldment. The ultrasonic inspection using the wedge angle was performed to understand the detection ability of fatigue cracks. In addition, the convolutional neural network was applied to minimize human error during the inspection. The results showed that the defects of connection weldment between the car body and bogie could be classified with more than 99.98% accuracy using CNN, and the effectiveness can be verified in the case of an inspection.

• Journal of the Korea Safety Management & Science
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• v.19 no.1
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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.