• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.1
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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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.6
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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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.

• The Journal of Information Systems
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• v.32 no.3
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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.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.3
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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.

• The Journal of Korea Robotics Society
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• v.18 no.2
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.709-710
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• 2013

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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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.

• Journal of the Korean Regional Science Association
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• v.38 no.3
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• pp.19-39
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• 2022

The aim of this study is to compare and analyze structural characteristics of smart city industry focused on Korea and Spain. Structural characteristics of industries were compared focusing on share, penetration, impact path and network clustering of smart industries. Research data used input-output tables established by Korea and Spain in 1995 and 2015, and industries were reclassified into 8 and 25 industries. The analysis model is the Smart SPIN Model. The key finding as follows: It was analyzed that there are differences in the structure and characteristics of the smart city industry between Korea and Spain. Firstly, It is analyzed that Korea has a larger share and penetration rate of IT manufacturing than Spain. On the other hands, Spain has a higher share and penetration rate in the IT service and knowledge service sectors than Korea. Secondly, Korea had many production paths for the IT service and the knowledge service. On the other hands, Spain included more production paths in the IT manufacturing sector. Thirdly, as a result of network analysis, Korea's smart industry has a characteristic that it is difficult to develop independently because it is dependent on traditional industries. In Spain, most of the smart industries were included in one industrial cluster, and it was analyzed to have an independent form. In conclusion, It was found that Korea has the industrial characteristics of a smart city based on IT manufacturing. Spain has the characteristics of smart city industry based on IT service and knowledge service. The results of this study are expected to provide basic data on the direction of smart city promotion and the establishment of smart city policies in Korea.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.