• 한국전기전자재료학회논문지
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• 제35권1호
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• pp.58-65
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• 2022

The field of liquid crystal display (LCD) is constantly in the spotlight and the process of depositing an alignment layer in the LCD manufacturing process is very important to obtain excellent performance such as low-power driving and high-speed response to improve LCD performance. Therefore, research on liquid crystal (LC) alignment is being actively conducted. When manufacturing LCD, it is necessary to consider the effect of the alignment layer thickness as one of the factors affecting various LCD performances. In addition, previous studies confirmed the LC alignment characteristics correlate with the rotation speed in the spin coating process. Therefore, the electro-optical properties of the LCD were investigated by manufacturing a polyimide alignment layer by varying the rotation speed in the spin coating process in this study. It was confirmed that the thickness of the polyimide alignment layer was controlled according to the spin coating conditions. The average transmittances of anti-parallel LC cells at the spin coating speed of 2,500 rpm and 3,000 rpm are about 60%, which indicates that the LC cell has relatively higher performance. At the spin coating speed of 3,000 rpm, the voltage-transmittance curve of twisted nematic (TN) LC cell was below 1.5 V, which means that the TN LC cell operated at a low power. In addition, high-speed operating characteristics were confirmed with a response time of less than 30 ms. From these derived data, we confirmed that the ideal spin coating speed is 3,000 rpm. And these results provide an optimized polyimide alignment layer process when considering enhanced future LCD manufacturing.

• 한국기계가공학회지
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• 제11권6호
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• pp.1-8
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• 2012

This study investigates stress and deformation due to static and dynamic vibration analysis about various types of bike handles installed with smart phone depositories. When force is applied on the side of handle at the models of type 1, 2, 3 and 4, the maximum equivalent stress is highest at type 2. The stress or deformation becomes lowest among these 4 model types. At vibration analysis, type 1 becomes safest within the range of 500Hz and type 3 becomes stable within the range of 100Hz. The result of this study can be applied with the design of bike handle installed with smart phone depository. The damage or deformation due to vibration can be prevented when the bike falls down. This result can be widely utilized to investigate and predict the durability.

• 산업경영시스템학회지
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• 제42권3호
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• 한국정보시스템학회지:정보시스템연구
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• 제32권3호
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• pp.205-224
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• 2023

Purpose This study investigates the impact of organizational characteristics on organizational performance through case studies of smart factory implementation in the context of Korean small and medium Enterprises (SMEs). To achieve this goal, this study adopts the smart factory index of KOSMO (Korea Smart Manufacturing Office) established by Korean Ministry of SMEs and Startups. We visited 3 firms implemented smart factory projects. This study presents the results of field study in detail with evaluation criteria on how organizational competences like AI technology adoption and facility automation can be exploited to positively influence organizational performance through smart factory implementation. Design/methodology/approach There are not so many results of empirical studies related to smart factories in Korea. This is because organizational support and user involvement are required for facility AI platform service beyond factory automation after the start of the 4th Industrial Revolution. Korean government's KOSMO (Korean Smart Manufacturing Office) has developed and proposed a level measurement index for smart factory implementation. This study conducts case studies based on the level measurement method proposed by KOSMO in the process of conducting case studies of three companies belonging to the root and mechanic industries in Korea. Findings The findings indicate that organizational competences, such as facility AI platform adoption and user involvement, are antecedents to influence smart factory implementation, while smart factory implementation has significant relationship with organizational performance. This study provides a better understanding of the connection between organizational competences and organizational performance through smart factory case studies. This study suggests that SMEs should focus on enhancing their organizational competences for improving organizational performance through implementing smart factory projects.

• 한국산업융합학회 논문집
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• 제24권3호
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• pp.351-361
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• 2021

This study proposes an intelligent control of manufacturing robot with dual arm based on neural network for smart factory implementation. In the control method of robot system, the perspectron structure of single layer based on neural network is useful for simple computation. However, the limitations of computation are emerging in areas that require complex computations. To overcome limitation of complex parameters computation a new intelligent control technology is proposed in this study. The performance is illustrated by simulation and experiments for manufacturing robot dual arm robot with eight axes.

• 로봇학회논문지
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• 제18권2호
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• pp.225-232
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• 2023

With the recent increase of multiple robots cooperating in smart manufacturing logistics environments, it has become very important how to predict the safety and efficiency of the individual tasks and dynamically assign them to the best one of available robots. In this paper, we propose a novel task policy learner based on deep relational reinforcement learning for predicting the safety and efficiency of tasks in a multi-robot manufacturing logistics environment. To reduce learning complexity, the proposed system divides the entire safety/efficiency prediction process into two distinct steps: the policy parameter estimation and the rule-based policy inference. It also makes full use of domain-specific knowledge for policy rule learning. Through experiments conducted with virtual dynamic manufacturing logistics environments using NVIDIA's Isaac simulator, we show the effectiveness and superiority of the proposed system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.709-710
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• 2013

• 한국기계가공학회지
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• 제21권9호
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• pp.21-27
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• 2022

The rotorcraft engine gearbox transmits the power generated by the turboshaft engine to the rotor by reducing the rotational speed and increasing the torque. The core of the rotorcraft engine gearbox is lightweight performance, which requires maximum weight reduction within the range that meets various requirements and constraints. Therefore, lightweight design through gear macro geometry optimization is necessary. In this study, gear macro geometry optimization was performed to reduce the weight of a rotorcraft engine gearbox. NSGA-III was used for the optimization, resulting in a combination of the gear ratio and macro geometry that minimizes the weight of the total gear. In addition, the safety factor of the gears satisfied the given conditions.

• 지역연구
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• 제38권3호
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• pp.19-39
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• 2022

본 연구의 목적은 한국과 스페인의 스마트시티 산업 특성을 비교 분석하는 것이다. 각 국가의 특성은 스마트 산업의 점유, 침투, 생산경로, 네트워크 클러스터를 중심으로 비교되었다. 연구의 자료는 1995년과 2015년의 한국 및 스페인의 투입산출표이며, 8개와 25개 산업으로 재분류되었다. 분석모형은 Smart SPIN Model을 활용하였다. 분석 결과는 다음과 같다. 첫째, 한국이 스페인보다 IT 제조업에서 점유율과 침투율이 더 높은 것으로 분석되었다. 반면, 스페인은 한국보다 IT 서비스업과 지식서비스업이 점유율 및 침투율 모두 더 큰 것으로 나타났다. 둘째, 생산경로 측면에서는 한국이 IT 서비스업과 지식서비스업이 스페인보다 높게 나타났으며, 스페인은 IT 제조업 분야가 더 많은 생산경로를 갖는 것으로 분석되었다. 셋째, 네트워크 분석 결과, 한국의 스마트 산업은 전통 산업에 종속되어있으며, 스마트 산업이 독자적으로 발달하기 어려운 특성이 있는 것으로 나타났다. 스페인은 스마트 산업의 대부분이 하나의 산업 클러스터로 나타나고 있어 독립적인 형태를 보이는 것으로 분석되었다. 즉, 한국은 IT 제조업 기반의 스마트시티 산업 특성을 가지며, 스페인은 IT 서비스와 지식서비스 기반의 스마트시티 산업 특성을 갖는 것으로 나타났다. 본 연구의 결과는 스마트시티 부문에서 있어 우리나라가 앞으로 나아가야 할 방향 및 정책 수립에 대한 기초자료를 제공해 줄 수 있을 것으로 기대한다.

• 융합정보논문지
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• 제11권4호
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• pp.83-101
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• 2021

본 연구는 우리나라 중소기업들에게 4차 산업혁명 대응과 스마트 기업으로의 변화를 위해서는 어떠한 기술들을 우선적으로 적용하여야 하는가에 대한 내용을 AHP를 활용하여 규명하는 것이다. 이를 위하여 4차 산업혁명 관련 기술들을 종합하고, 김대훈 외(2019)의 분류기준을 준용하지만 전문가들의 의견을 추가로 수렴하여 관련 기술들을 분류하였다. 인공지능(AI), Big Data, Cloud Computing을 디지털 기반기술로, 모바일, 사물인터넷(IoT), Block Chain을 초연결 기술로, 무인운송(자율주행), 로봇(Robot), 3D 프린팅, 드론을 융합기술로, 스마트 제조 및 물류, 스마트 헬스케어, 스마트 교통, 스마트 금융을 스마트 산업기술로 구분하였다. AHP 분석과 종합가중치를 계산하는 방식으로 기술적용 우선순위를 확인한 결과 제조기업은 모바일, 인공지능(AI), Big Data, 로봇(Robot)의 순위가 높으며, 서비스기업은 Big Data, 로봇(Robot), 인공지능(AI), 스마트 헬스케어의 순위가 높고 전체기업에서는 Big Data, 인공지능(AI), 로봇(Robot), 모바일의 순서이다. 본 연구를 통해 4차 산업혁명 대응과 스마트 기업으로의 변화를 위해서는 어떠한 기술들을 우선적으로 적용하여야 하는가를 명확하게 규명하였다.