• Journal of Korea Society of Industrial Information Systems
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• v.26 no.1
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• pp.21-29
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• 2021

The emerging smart world based on IoT requires deployment of a large number of diverse sensors to generate data pertaining to different applications. Recent years have witnessed a plethora of IoT solutions beneficial to various application domains, IoT techniques also help boost agricultural productivity by increasing crop yields and reducing losses. This paper presents a predictive IoT smart farm platform for forcast services. We built an online agricultural forecasting service that collects microclimate data from weather stations in real-time. To demonstrate effectiveness of our proposed system, we designed a frost and pest forecasting modes on the microclimate data collected from weather stations, notifies the possibilities of frost, and sends pest forecast messages to farmers using push services so that they can protect crops against damages. It is expected to provide effectively that more precise climate forecasts thus could potentially precision agricultural services to reduce crop damages and unnecessary costs, such as the use of non-essential pesticides.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.115-123
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• 2021

Manufacturing execution system is a factory information system that handles production-related quality data as well as executes production plans of process unit for all resources in the production process on site. As the 4th industrial revolution, which maximizes an automation and connectivity with artificial intelligence, has become a hot topic, manufacturers are showing interest in building a smart factories, but enormous construction costs and unstandardized production processes are obstacles to smart factory construction. Therefore, this paper designs and implements a manufacturing execution system for building a smart factory in a deterioration factory. we propose a Web-based manufacturing execution system aiming at a smart factory at the basic level for steel wire processing. The proposed system will smoothly support interworking with the existing ERP system using REST APIs, and will consider extensibility so that it can be used in various devices and browsers. We will show practicality by implementing the proposed WoT-based manufacturing execution system.

• Journal of Platform Technology
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• v.6 no.3
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• pp.47-54
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• 2018

Predictive analysis in the hardware industry can be performed at an appropriate point in time to prevent failure of production facilities and reduce management costs. This helps to perform more efficient and scientific maintenance through automation of failure analysis. Among them, predictive management aims to prevent the occurrence of anomalous state by identifying and improving the abnormal state based on the gathering, analysis, and scientific data management of facilities using information technology and constructing prediction model do. In this study, we made a fault tree through the Relex tool and analyzed the error code of the hardware to study the safety.

• The Journal of Bigdata
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• v.4 no.1
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• pp.129-142
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• 2019

Construction projects have experienced many failures due to incomplete production environments. Thus, the purpose of this study is to use ICT resources leased during the construction period at the construction site and to introduce the Mobile Cloud Computing Service, which utilizes Cloud Computing Service and mobile devices such as smart phones, tablet PCs, and notebooks instead of physically wired communication networks. The characteristics of Mobile Cloud, such as rapid accuracy, shared collaboration, and ubiquity, will affect the social network among various construction site participants. we conducted empirical research on the introduction of Mobile Cloud to promote information exchange and convergence among the participants and mutual trust, ultimately improving the project performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.803-804
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• 2016

With the advent of Germany's Industry 4.0, research of smart factory to applying the ICT in manufacturing industries is in progress. But the current system controlled equipment using the data declared in the embedded systems. In this paper, we proposed equipment control method to implement smart factory based on IoT. This method is create D/B table of data declared in equipment. and equipment shall call all of control unit parameters. When using the present method, it is possible to efficiently control the number of equipment as less network resource. Also It can operating a factory efficiently.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.113-115
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• 2015

최근 ICT/loT 기술들이 다양한 산업분야에 적용하는 사례가 늘어나고 있는 추세이다. 특히 노동 집약적인 농업 분야에도 다양한 형태로 적용되고 있지만, 대내외적으로 복잡하게 얽혀 있는 농업/농촌의 활성화를 위해서는 다른 방안 제시가 필요하다, 본 논문에서는 1차 산업을 중심으로 2차, 3차 산업과 연계 또는 융복합하여 영세 규묘의 지역 농가들 및 업체들의 클러스터화를 통해 새로운 고부가가치를 창출 시킬 수 있는 6차 산업화를 지원할 수 있는 통합 지원 플랫폼을 제안하였다. 제안된 통합 지원 플랫폼은 육묘의 품질 관리 단계에서 최종 소비자에 이르는 전 과정을 지원하는 통합 지원할 수 있는 서비스 플랫폼이다. 육묘, 생산, 가공, 유통/수출, 체험/관광, 판매, 소비에 이르는 전체 시스템을 단계적으로 연결하고, 통합 운영/관리될 수 있도록 함으로써, 농식품에 대한 신뢰도 및 지역 농가 및 지역 농촌의 경제활성화에 도움을 줄 수 있도록 하였다.

• Journal of Korea Technology Innovation Society
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• v.19 no.3
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• pp.545-571
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• 2016

The development of ICT brings a big change in manufacturing industries, and new information technology such as IoT, AR, and big data was applied on manufacturing process. As a result, the concept of smart factory has been introduced as a new manufacturing paradigm. In fact advanced countries like USA, Germany, and Japan have actively introduced smart factory in their manufacturing industries such as electronic, automobile, machinery, to improve production efficiency and quality. The manufacturing environment has been changed into flexible system, so that smart factory will be leading future manufacturing industries. Thes changes have more severe influence on Korean manufacturing industries. Mny industrial companies, have a strong interest in smart factory and they, particularly big enterprises, have been adopting smart factory to increase their manufacturing efficiencies. However, Korean small and medium-sized enterprises (SMEs) have many financial and technological difficulties so that the diffusion of smart factory in Korean SMEs has not been satisfiable up to present. However, smart factory is very important for enhancing their competitiveness in global market. Therefore, this study aims at identifying the standardization strategy of smart factory in so-called Korean 'roots industry' by presuming that the standardization will activate the diffusion of smart factory among Korean SMEs. For this purpose, first, this study examines the competitiveness of SMEs, especially in 'roots industry' and identifies the necessity of diffusion of smart factory among those SMEs. Second, based on the active review on the existing literature, this study identifies four factor groups that would influence the adoption or diffusion of standardized smart factory. They are technological, organizational, industrial and policy factors. Third, using those four factors, this study made two comprehensive case analyses on the adoption and diffusion of smart factory. These two companies belong to molding sector which is one of the important six sectors in 'root industry'. Finally, based on the theoretical and empirical analyse, this study suggests four strategies for activating the standardization of smart factory; international standardization, government-leading standardization, firm-leading standardization, and non-standardization.

• Convergence Security Journal
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• v.22 no.5
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• pp.69-80
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• 2022

Now that climate change and food resource security are becoming issues around the world, smart farms are emerging as an alternative to solve them. In addition, changes in the production environment in the primary industry are a major concern for people engaged in all primary industries (agriculture, livestock, fishery), and the resulting food shortage problem is an important problem that we all need to solve. In order to solve this problem, in the primary industry, efforts are made to solve the food shortage problem through productivity improvement by introducing smart farms using the 4th industrial revolution such as ICT and BT and IoT big data and artificial intelligence technologies. This is done through the public and private sectors.This paper intends to consider the minimum requirements for the smart farm data collection system for the development and utilization of smart farms, the establishment of a sustainable agricultural management system, the sequential system construction method, and the purposeful, efficient and usable data collection system. In particular, we analyze and improve the problems of the data collection system for building a Korean smart farm standard model, which is facing limitations, based on in-depth investigations in the field of livestock and livestock (pig farming) and analysis of various cases, to establish an efficient and usable big data collection system. The goal is to propose a method for collecting big data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.338-343
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• 2018

Recently, a computer numerical control (CNC) machine is used widely for mold making in various industries. In the operation of a CNC machine, the production quality and safety of workers are becoming increasingly important as the product process increases. A variety of tool life prediction studies has been conducted to standardize the quality of production and improve reproducibility. When the tool life is predicted using the conventional tool life equation, there is a large error between the experimental result and result by the conventional tool life equation. In this paper, an algorithm that can predict the precise tool life was implemented using a genetic algorithm.

• Journal of Technology Innovation
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• v.23 no.3
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• pp.67-85
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• 2015

This study investigates the relationships among SMEs' innovation capacity, standardization education activities, and performances. Employing about 900 SMEs in the ICT and electronics electricity industries, this study used regression analysis and examined the effects of standardization education activities on performance and the moderating effect of innovation capacity. The results indicate that standardization education activities positively affect SMEs' production and quality improvement and R&D activity improvement. The results also show that R&D investment ratio moderates the relationship between standardization education and production and quality improvement. This study provides practical insight into why firm managers should pay attention to standardization education and innvation capacity to improve firm performance.