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방선호(Sunho Bang),백승(Seung Baek) 한국자동차공학회 2011 한국자동차공학회 학술대회 및 전시회 Vol.2011 No.11
Snap-fit is an effective method to provide a simple, economical, and rapid mean of attaching thermoplastic parts to other plastic materials or metals. Designers can dramatically reduce production and component costs in fastening and assembly of both plastic and non-plastic parts by taking advantage of the design possibilities of thermoplastics. This paper discusses an optimized snap-fit in Guide-bracket of Bumper-fascia to assemble easily and to dissemble efficiently over a defined loading. It is mainly used in ABAQUS Software considered the nonlinear material property of polymer.
방선호(Sunho Bang),이창건(Changkun Lee) 한국자동차공학회 2010 한국자동차공학회 학술대회 및 전시회 Vol.2010 No.11
Snap-fit is an effective method to provide a simple, economical, and rapid mean of attaching thermoplastic parts to other plastic materials or metals. Designers can dramatically reduce production and component costs in fastening and assembly of both plastic and non-plastic parts by taking advantage of the design possibilities of thermoplastics. The flexibility of thermoplastics permit simple, efficient designs, so snap-fit can be designed to allow parts to be either permanently fastened or frequent assembly and disassembly. This research is to develop a frequent assembly optimized snap-fit in outside rearview mirror (OSRVM) using design of experiments (DOE) in simulation. The simulation is mainly used in ABAQUS Software considered the nonlinear material property of polymer.
김동윤 ( Dongyun Kim ),방선호 ( Sunho Bang ),장지영 ( Jiyoung Jang ),신광섭 ( Kwangsup Shin ) (사)한국빅데이터학회 2021 한국빅데이터학회 학회지 Vol.6 No.2
COVID-19의 대유행은 컨테이너를 사용하는 국가 간 수출입 물동량 불균형을 더욱 악화시켰으며, 이는 공컨테이너 수급의 문제까지 이어지게 되었다. 적정 수요만큼의 공컨테이너 확보는 안정적이고 효율적인 항만 운영을 위해 필수적인 요소이다. 지금까지 여러 기법을 사용한 공컨테이너 수요예측 방안이 연구되어 왔다. 그러나 항만 및 선사에서 직접 활용 가능한 수요예측 보다는 월 혹은 연 단위의 장기적인 예측에 머루르고 있었다. 본 연구에서는 실제 인공신경망을 이용한 일별, 주별 단위 예측 방안을 제시한다. 이를 위해 머신러닝 기법 중 다층 퍼셉트론과 회귀분석을 활용하여 수요예측을 진행하였으며, 데이터 부족 문제를 해결하기 위해 적컨테이너와 공컨테이너의 입항 후 다시 항만으로 유입되는 과정을 기반으로 데이터를 재가공하였다. 이를 통해, 정확도가 매우 높지는 않지만, 현장에서는 활용 가능한 일별 및 주별 수요 예측 모델을 개발할 수 있었다. The pandemic of COVID-19 further promoted the imbalance in the volume of imports and exports among countries using containers, which worsened the shortage of empty containers. Since it is important to secure as many empty containers as the appropriate demand for stable and efficient port operation, measures to predict demand for empty containers using various techniques have been studied so far. However, it was based on long-term forecasts on a monthly or annual basis rather than demand forecasts that could be used directly by ports and shipping companies. In this study, a daily and weekly prediction method using an actual artificial neural network is presented. In details, the demand forecasting model has been developed using multi-layer perceptron and multiple linear regression model. In order to overcome the limitation from the lack of data, it was manipulated considering the business process between the loaded container and empty container, which the fully-loaded container is converted to the empty container. From the result of numerical experiment, it has been developed the practically applicable forecasting model, even though it could not show the perfect accuracy.
Knee Air Bag 전개를 고려한 Knee Bolster System 최적화 연구
선광상(Kwangsang Seon),방선호(Sunho Bang),박상근(Sangkeun Park),김용석(Yongsuk Kim) 한국자동차공학회 2014 한국자동차공학회 학술대회 및 전시회 Vol.2014 No.11
automotive industry has steadily tried to reduce the Vehicle weight to improve fuel. there have been studied aiming at reducing weight by changing thickness or new lightweight material. in this study, we took both thickness and material arrangement as design variables to enhance reducing the weight. this study suggest optimized knee bloster system concept model considering FMVSS208 regulation with Air Bag Module Bracket stiffness without mass increase. design factor, are selected and the intersection is evaluated among design factors using function analysis of DFSS. multi-disciplinary optimization process is conducted to get the optimal design. the validation runs are carried over to achieve the resonable design solution to implement the optimal solution to the physical vehicle proprietary optimization tool.
Decklid Beavertail stiffness 향상을 위한 Parameter Study
선광상(Kwangsang Seon),방선호(Sunho Bang) 한국자동차공학회 2012 한국자동차공학회 부문종합 학술대회 Vol.2012 No.5
The decklid is mainly used in sedan style vehicle. It is open and close system to input luggage and cover the luggage room. If the decklid has weak stiffness, It will be deformed during painting process. And Deformed Decklid will cause a Fit & Flushness issues. These problem affects manufacturing firm’s image and vehicle quality. Accordingly, we have to improve the stiffness of decklid. This paper is the study about sensitivity analysis of decklid’s design variable. In this research we analyze the sensitivity of each design variable. And we expect reduction of time and cost to modify the decklid that is build. This result can be applied to design of Decklid. we suggested that the effective control factors of decklid.