• Title/Summary/Keyword: Auto Industry

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Vehicles Auto Collision Detection & Avoidance Protocol

  • Almutairi, Mubarak;Muneer, Kashif;Ur Rehman, Aqeel
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.107-112
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    • 2022
  • The automotive industry is motivated to provide more and more amenities to its customers. The industry is taking advantage of artificial intelligence by increasing different sensors and gadgets in vehicles machoism is forward collision warning, at the same time road accidents are also increasing which is another concern to address. So there is an urgent need to provide an A.I based system to avoid such incidents which can be address by using artificial intelligence and global positioning system. Automotive/smart vehicles protection has become a major study of research for customers, government and also automotive industry engineers In this study a two layered novel hypothetical approach is proposed which include in-time vehicle/obstacle detection with auto warning mechanism for collision detection & avoidance and later in a case of an accident manifestation GPS & video camera based alerts system and interrupt generation to nearby ambulance or rescue-services units for in-time driver rescue.

Outlier Detection and Labeling of Ship Main Engine using LSTM-AutoEncoder (LSTM-AutoEncoder를 활용한 선박 메인엔진의 이상 탐지 및 라벨링)

  • Dohee Kim;Yeongjae Han;Hyemee Kim;Seong-Phil Kang;Ki-Hun Kim;Hyerim Bae
    • The Journal of Bigdata
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    • v.7 no.1
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    • pp.125-137
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    • 2022
  • The transportation industry is one of the important industries due to the geographical requirements surrounded by the sea on three sides of Korea and the problem of resource poverty, which relies on imports for most of its resource consumption. Among them, the proportion of the shipping industry is large enough to account for most of the transportation industry, and maintenance in the shipping industry is also important in improving the operational efficiency and reducing costs of ships. However, currently, inspections are conducted every certain period of time for maintenance of ships, resulting in time and cost, and the cause is not properly identified. Therefore, in this study, the proposed methodology, LSTM-AutoEncoder, is used to detect abnormalities that may cause ship failure by considering the time of actual ship operation data. In addition, clustering is performed through clustering, and the potential causes of ship main engine failure are identified by grouping outlier by factor. This enables faster monitoring of various information on the ship and identifies the degree of abnormality. In addition, the current ship's fault monitoring system will be equipped with a concrete alarm point setting and a fault diagnosis system, and it will be able to help find the maintenance time.

The Role of Space-based Social Capital in Retailing Industrial Cluster: The case study of Dondaemun-gu Dapsimni Auto-parts shopping area (유통산업 집적지에서 장소기반 사회자본의 역할: 동대문구 답십리 자동차 부품상가를 사례로)

  • Ko, Byeungok
    • Journal of the Economic Geographical Society of Korea
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    • v.19 no.3
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    • pp.457-473
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    • 2016
  • This research investigates that role of space-based social capital presented in Dapsimni auto-parts shopping area considering Korean auto-parts industry and the regional characteristics of retailing industrial cluster. For this, it went through the process with in-depth interview and surveys of the owner of Dapsimni, social capital of retailing industrial cluster studied using Lin(1999)'s social capital model by separating formation, accessibility and mobilization of it. The result is that auto-part sellers in Dapsimni make themselves space-based social capital, which provides the profit from certain area: strengthening auto-parts of transaction cost and information exchange among them, creating new market for selling auto-parts. This meant that main factor sustaining the characteristic of retailing industrial cluster despite gradually decline of its role.

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A Study on Quality Assurance in Auto-parts Research & Development Stage with APQP and DFSS (APQP와 DFSS를 연계한 자동차부품연구개발 단계에서 품질보증에 관한 연구)

  • Lee, Kang-In;Kim, Jae-Hyu
    • Journal of Korean Society for Quality Management
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    • v.39 no.1
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    • pp.131-140
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    • 2011
  • Today, due to the global recession car sales have been decreased rapidly and auto makers are competing continuously to expand their market share. Automakers are struggling in order to secure competitive cost and quality through continuous cost reduction and quality innovation activities to win in the competition. In this situation, auto parts makers are trying to reinforce price competitiveness by reducing COPQ (Cost Of Poor Quality) in the mass production stages by securing the quality of components in advance from the design stage through DFSS (Design For Six Sigma) activities which is 6 sigma approach in the R&D field. However, auto parts makers have been undergone various confusion, feeling difficulties to get interrelationship among various activities. Thus, this study is going to suggest approach method for much more effective R&D activities by securing interrelationship between ISO/TS 16949 system established in the auto parts industry and DFSS activities.

Design of Integrated Database for CRM in Automobile Maintenance Industry

  • Jung, Lee-Sang;Jung, Dae-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.5
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    • pp.55-63
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    • 2018
  • In this paper, we designed a system that integrate and organize customer management programs and databases, which are performed independently of each other. And we designed the system so that it can be used for future marketing by implementing the system to share and efficiently utilize mutual independent maintenance information. From the CRM perspective, a comprehensive information system ghat manages every information on both new cars and second hand cares grom their purchase, to parts, to insurance, and to scraping needs to be established. The following should be applied in the establishment of the IAMS. Auto makers or auto maintenance services providers exclusive management of information on customers and their car maintenance services is aggravating the customer's inconvenience and complaints. In addition, the service provider has difficulty providing consistent maintenance services because it has little information about previous auto maintenance services the customer received. Besides, the customers who have no information on costs of parts and labor tend to hesitate to trust the costs of maintenance services. This study to provide customers with systematic maintenance service and causing them some inconvenience. Therefore, in order to maintain existing customers, auto maintenance service providers should provide services the customers wanted on the basis of accurate information about them.

Load Prediction using Finite Element Analysis and Recurrent Neural Network (유한요소해석과 순환신경망을 활용한 하중 예측)

  • Jung-Ho Kang
    • Journal of the Korean Society of Industry Convergence
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    • v.27 no.1
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    • pp.151-160
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    • 2024
  • Artificial Neural Networks that enabled Artificial Intelligence are being used in many fields. However, the application to mechanical structures has several problems and research is incomplete. One of the problems is that it is difficult to secure a large amount of data necessary for learning Artificial Neural Networks. In particular, it is important to detect and recognize external forces and forces for safety working and accident prevention of mechanical structures. This study examined the possibility by applying the Current Neural Network of Artificial Neural Networks to detect and recognize the load on the machine. Tens of thousands of data are required for general learning of Recurrent Neural Networks, and to secure large amounts of data, this paper derives load data from ANSYS structural analysis results and applies a stacked auto-encoder technique to secure the amount of data that can be learned. The usefulness of Stacked Auto-Encoder data was examined by comparing Stacked Auto-Encoder data and ANSYS data. In addition, in order to improve the accuracy of detection and recognition of load data with a Recurrent Neural Network, the optimal conditions are proposed by investigating the effects of related functions.

A Box Office Type Classification and Prediction Model Based on Automated Machine Learning for Maximizing the Commercial Success of the Korean Film Industry (한국 영화의 산업의 흥행 극대화를 위한 AutoML 기반의 박스오피스 유형 분류 및 예측 모델)

  • Subeen Leem;Jihoon Moon;Seungmin Rho
    • Journal of Platform Technology
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    • v.11 no.3
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    • pp.45-55
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    • 2023
  • This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

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A Study on the Implementation of Distributed MRP to Increase the Utilization of the MES System in the Automobile Parts Manufacturing Industry (자동차부품 제조업의 MES 시스템 활용도를 높이기 위한 분산형 MRP 구현에 관한 연구)

  • Nam, Eun-Jae;Kim, Kwang-Soo
    • Journal of the Korea Safety Management & Science
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    • v.24 no.2
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    • pp.127-134
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    • 2022
  • Production management in the automobile parts industry is carried out according to the production plan of the customer, so it is important to prevent shortages in product supply. As the product composition became increasingly complex, the MES System was built for the purpose of efficient production plan management and inventory management, but its utilization is low. This study analyzed the problems of the MES system and sought to improve it. Through previous studies, it was confirmed that the inventory management of the pull approach that actually occurred in the warehouse is more suitable than the push approach based on the forecast of the warehouse for the volatility, complexity, and uncertainty of orders in the auto parts industry. To realize this, we tried distributed MRP by using the ADO function of VBA to link the standard information of the MES system with Excel and change the structure of the BOM table. Through this, it can help increase the accuracy of production planning and realize efficient inventory management, thereby increasing the utilization of the MES system in the auto parts industry and enhancing the competitiveness of the company.

Optimal Design of an Auto-Leg System for Washing Machines (세탁기용 자동신통저감장치($Auto-Leg^{TM}$)의 최적 설계)

  • Seo, H.S.;Lee, T.H.;Jeon, S.M.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2006.05a
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    • pp.996-1001
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    • 2006
  • Automatic washing machines have been improved and popularized steadily since the first electric washing machine was produced in the early 1900's. Appliance industry has tried to obtain the performance of washing machine with large capacity, high energy efficiency, low vibration and low noise levels. As the installation peace of a washer becomes closer to the living space, vibration and noise problems become more important challenges. In general, a washing machine has four legs to support its body. Four legs of the washing machine should be attached on a floor. If not so, it may cause severe vibration or walking in the spin-drying process. Unfortunately, the floor of an ordinary house is bumpy in general, and the consumers will not accept bolting washing machines to a foundation; moreover, sometimes they move the location of their washing machines to utility rooms or bath rooms or kitchens and don't care for leveling the legs exactly. In this study, we devise an auto-leg system that prevents the occurrence of abnormal vibration and walking of washing machines. It is simply composed of a spring and a friction damper. Some experiments are implemented to show the dynamic characteristics of the three-dimensional auto-legged washing machine model that is located on the even or uneven ground. A spring parameter is optimized to adjust the length of the auto-leg system automatically up to 10 mm irregularity, and the friction damper is designed to decrease a resonance induced by the spring of the auto-leg system. Some numerical results show that placing the proposed auto-leg system in a washing machine makes good performance with low vibration, as well as low noise, regardless of the unevenness of the floor.

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