• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.274-280
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• 2017

The smart-car industry has emerged as the important variable that will decide the future industrial contour of the automotive industry, together with commercialization of electronic vehicles, connected cars, infotainment, telematics, and the autonomous/self-driving car. This study analyzes the strategic position of platform companies and car manufacturers that would determine the future of the smart-car market. The findings of this study show that despite the entry barriers in industrial factors, such as economies of scale, the industrial infrastructure, and global production networks, and technical factors like exclusive head-sector information, car manufacturers may be deprived of their industrial leadership by platform companies with map and user data, big data capabilities, and user interface experience if they lag behind ICT innovation. This insight is based on the emerging importance of software and platforms, and the simplification of car structures, proven by the successful commercialization of electronic vehicles. This study complements existing studies mainly focused on technical aspects of the smart-car industry by examining the strategic dimensions of platform companies and their approach to the future smart-car market by comparing them with existing car manufacturing multinationals.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.21-26
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• 2020

An autonomous driving system is based on the deep learning system built by big data which are obtained by various IoT sensors. The miniaturization and high performance of the IoT sensors are needed for diverse devices including the autonomous driving system. Specially, the miniaturization of the sensors leads to compel the miniaturization of the fixer structures. In the viewpoint of the miniaturization, metallic structure is a best solution to attach the small IoT sensors to the main body. However, it is hard to manufacture the small metallic structure with a conventional machining process or manufacturing cost greatly increases. As one of solutions for the problems, in this work, metallic FDM (Fused depositon modeling) based on metallic filament was proposed and the FDM process was investigated to fabricate the small metallic structure. Final part was obtained by the post-process that consists of debinding and sintering. In this work, the relationship between infill rate and the density of the part after the post-process was investigated. The investigation of the relationship is based on the fact that the infill rate and the density obtained from the post-processing is not same. It can be said that this work is a fundamental research to obtain the higher density of the printed part.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.138-143
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• 2023

In this study, the crack healing performance of each crack healing agent manufacturing method was analyzed by adding crack healing agents in the form of alginate gel and spore suspension inoculated with endospores of calcium carbonate-forming bacteria to mortar. In addition, by applying it to an full-scale structure in the form of a box-type culvert, we attempted to create an environment in which the developed crack healing agent can be applied not only to a laboratory environment but also to an actual field. The crack healing agent using the dry heat drying method showed crack healing performance, but in the case of the freeze drying method, many spores were killed by freeze hardening and therefore the crack healing performance was lost. As a result of SEM and XRD pattern analysis of the presumed crack healing material extracted from the crack of a full-scale structure, it was found to be calcite, one of the calcium carbonate crystals produced by microorganisms applied to the crack healing agent. In conclusion, it was found that the crack healing by microorganisms can be implemented in a real structure.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.109-120
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• 2020

The supply chain without digitization is just a series of discrete, siloed steps taken through marketing, product development, manufacturing, and logistics, and finally into the hands of the customer. Digitization brings down those walls, and the chain becomes a completely integrated network fully transparent to all the parties involved. The ulitimate goals of digitizatized supply chain management are velocity and visibility. This network will depend on a number of key technologies including integrated planning and execution systems, supply chain analytics, autonomous logistics, smart warehousing and factory, etc, enabling companies to react to disruptions in the supply chain, and even anticipate them, by fully modeling the network, creating "what-if" scenarios, and adjusting the supply chain in real time as conditions change. This paper presents a number of studies on digitalization of supply chains and provides a discussion on issues raised in the process of technology adoption. Implications of the study findings are also provided.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.399-409
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• 2016

Recent automotive market is changing rapidly with eco-friendly, fuel-efficient, unmanned autonomous. In order to grow domestic automotive industry, various companies such as IT, marketing, advertising/PR, production/manufacturing, distribution have to need the fused global value chain(GVC) production system. The purpose of this study is that Small parts makers will look for support measures to enter the GVC of global automakers. To this end, to examine the status and cooperation between vehicle manufacturers and component suppliers in GVC. Part SMEs will look for Realistic and possible support policy direction needed to enter the carmakers GVC. In order that the small parts company have to enter the GVC of the car manufacturers in the automotive industry, the small parts company should understand the nature and governance of large corporations that operate the GVC, and develop a tailored strategy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.385-393
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• 2016

This paper presents the new position estimation method which contains the optical displacement sensor and the dead reckoning based position estimation algorithm for automation of hull cleaning robot. To evaluate feasibility of the proposed position estimation method on the hull cleaning robot, it was applied on the small scale robot model which has an identical drive method with the hull cleaning robot and then a set of the position estimation experiments were performed. The experimental results of the position estimation demonstrate that the estimated results with the optical displacement sensors is more accurate than used rotary encoder method. In addition, it continuously calculated the robot position quite close to the real robot driving path. In a follow-up study, the proposed position estimation method will be complemented and exploited on the actual hull cleaning robot by adding additional sensor modules that correct measurement errors.

• Tunnel and Underground Space
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• v.29 no.1
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• pp.1-11
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• 2019

This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.33-39
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• 2021

In this study, there are regional limitations for the fine dust data provided by public data to represent the wide area air quality. It is about a method that can provide detailed data in a specific area beyond location restrictions. The goal of this implementation is to mount the IoT-based fine dust sensor on a quadcopter that can fly autonomously beyond the positional limitations of the current measuring station, which is fixed, and quickly move the fire-generating area and the area of rapid fine dust to make detailed measurements. Through this, the system is designed and implemented to enable the fundamental analysis of the occurrence. We designed a QDMS system and proposed a method to measure detailed changes in fine dust at a specific location through manufacturing and experiments.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.168-172
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• 2018

HACCP is scientific Sanitary control system to ensure food safety with autonomous, systematic and effective way by analysing hazard element that can be occurred in each steps until an end consumer takes food including raw material status, manufacturing, processing, storing, distributing, cooking and specifying the critical control point. In this paper, the temperature and humidity are measured during the transport of food, the stage of its distribution, to ensure systematic and effective management of HACCP, and we designed a monitoring terminal that uses this information to send it to servers periodically and a firmware that implements it. We have confirmed that the data transmitted by the terminal, including the information measured in sub-net, was well stored on the server and the response from the server is well received by the terminal. It is expected to be used for the management of food history, data tracking and statistical data in the future. This system is also considered to be an applicable system for group cafeteria such as schools or workplaces and logistics warehouses for raw materials or food storage and so on.