• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.149-162
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• 2021

This paper established a new smart factory based on manufacturing data for an introductory company focusing on the personalized cosmetics manufacturing industry. We build on an example of a system that collects, manages, and analyzes documents and data that were previously managed by CGMP-based analog for data-driven use. To this end, we have established a system that can collect all data in real time at the production site by introducing artificial intelligence smart factory platform LINK5 MOS and POP system, collecting PLC data, and introducing monitoring system and pin board. It also aims to create a new business cluster space based on this project.

• 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 the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.55-59
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• 2018

Big-data, a revolutionary technology in the era of the 4th Industrial Revolution, provides services in various fields such as health, public sector, distribution, marketing, manufacturing, etc. It is very useful technology for marketing analysis and future design through accurate and quick data analysis. It is very likely to develop further. However, the biggest problem when using Big-data is privacy and privacy. When various data are analyzed using Big-data, the tendency of each user can be analyzed, and this information may be sensitive information of an individual and may invade privacy of an individual. Therefore, in this paper, we investigate the necessary measures for Personal private information infringement that may occur when using Personal private information in Big-data environment, and propose necessary Personal private information protection technologies to contribute to protection of Personal private information and privacy.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.23-28
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• 2017

For manufacturing industry to achieve efficient manufacturing process, improving a company's productivity and reducing cost is a required task of the current manufacturing companies. For design of efficient manufacturing process and improvement of productivity, efficient manufacturing process method is studied through removal of unnecessary elements analyzing motions and using test-bed linkage system based on virtual reality. When building process line after verifying optimization through virtual process arrangement simulation in advance, it is available to save additional cost for process modification or supplement to result in practical effects of improving a company's manufacturing competition. Reducing design period, improving equipment, making automation, realizing ergonomics, and improving process through this study, it will be available to achieve improvement of productivity, enhancement of quality, cost reduction as well as employees' satisfaction for safety and health.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.259-269
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• 2017

As emerging the '4th Industrial Revolution' by increasing the necessity of the intelligent system recently, 'Autonomic Control System' also has been the important issue. It is necessary to develop the system collecting data of machines and sensors for the autonomic control system to monitor the target system. But it is difficult to collect data because data formats of machines and sensors of the existing factories differ between each manufacturer. Therefore, this paper presents and implements data collecting and processing system that comprise 3 steps including 'ParseBuffer', 'ProcessData' and 'AddToBuffer' by using 'MTConnect' that is standard manufacturing facility data collecting middleware. Through the suggested system, we can get data in a common format usable in an autonomous control system. As a case study, we experimented with the generation and collection of AGV (Automated Guided Vehicle) data, which is an unattended transportation system in the factory. To accomplish this, we defined the data type in accordance with the MTConnect standard and confirmed the data collected through the proposed system.

• Korea Science and Art Forum
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• v.21
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• pp.31-43
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• 2015

Information and Communications Technology (ICT) is one of the technologies which represent the core value of the creative economy. It has served as a vehicle connecting the existing industry and corporate infrastructure, developing existing products and services and creating new products and services. In addition to the ICT, new devices including big data, mobile gadgets and wearable products are gaining a great attention sending an expectation for a new market-pioneering. Further, Internet of Things (IoT) is helping solidify the ICT-based social development connecting human-to-human, human-to-things and things-to-things. This means that the manufacturing-based hardware development needs to be achieved simultaneously with software development through convergence. The essential element the convergence between hardware and software is OS, for which world's leading companies such as Google and Apple have launched an intense development recognizing the importance of software. Against this backdrop, the status-quo of the software market has been examined for the study of the present report (Korea Evaluation Institute of Industrial Technology: Professional Design Technology Development Project). As a result, the software platform-based Google's android and Apple's iOS are dominant in the global market and late comers are trying to enter the market through various pathways by releasing web-based OS and similar OS to provide a new paradigm to the market. The present study is aimed at finding the way to utilize a smart content by which anyone can be a developer based on OS responding to such as social change, newly defining a smart content to be universally utilized and analyzing the market to deal with a rapid market change. The study method, scope and details are as follows: Literature investigation, Analysis on the app market according to a smart classification system, Trend analysis on the current content market, Identification of five common trends through comparison among the universal definition of smart content, the status-quo of application represented in the app market and content market situation. In conclusion, the smart content market is independent but is expected to develop in the form of a single organic body being connected each other. Therefore, the further classification system and development focus should be made in a way to see the area from multiple perspectives including a social point of view in terms of the existing technology, culture, business and consumers.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.211-220
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• 2022

Recently, research on smart factories triggered by the 4th industrial revolution is being actively conducted. Accordingly, the manufacturing industry is conducting various studies to improve productivity and quality based on deep learning technology with robust performance. This paper is a study on the method of detecting tire surface defects in the visual inspection stage of the tire manufacturing process, and introduces a tire surface defect detection method using a depth image acquired through a 3D camera. The tire surface depth image dealt with in this study has the problem of low contrast caused by the shallow depth of the tire surface and the difference in the reference depth value due to the data acquisition environment. And due to the nature of the manufacturing industry, algorithms with performance that can be processed in real time along with detection performance is required. Therefore, in this paper, we studied a method to normalize the depth image through relatively simple methods so that the tire surface defect detection algorithm does not consist of a complex algorithm pipeline. and conducted a comparative experiment between the general normalization method and the normalization method suggested in this paper using YOLO V3, which could satisfy both detection performance and speed. As a result of the experiment, it is confirmed that the normalization method proposed in this paper improved performance by about 7% based on mAP 0.5, and the method proposed in this paper is effective.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.105-111
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• 2017

With the emergence of the fourth industrial revolution, more and more attempts have been made to apply IoT technology to the manufacturing process and launch the product. In this paper, we propose IoT authentication scheme based on hash chain which can easily apply IoT device to small and medium enterprises in Korea. In the proposed method, the companies that installed IoT devices suitable for the manufacturing environment are selected to maintain the linkage between IoT devices so that product information and release information can be efficiently collected and managed during the entire manufacturing process. In addition, the proposed scheme is characterized in that it does not require an additional encryption / decryption algorithm because the authentication information of the IoT device is constructed based on a hash chain. As a result of the performance evaluation, the efficiency of the manufacturing process was improved by 18.5% and the processing of the manufacturing process with the IoT device was shortened by 20.1% on the average according to the application of the IoT device. In addition, the labor cost reduction costs in the manufacturing process decreased by an average of 30.7%.

• Journal of Industrial Convergence
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• v.1 no.1
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• pp.159-169
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• 2003

In the 21st century, a time for smaller companies is fast approaching. A lot of people believe that the small and mid-sized companies will be a main force for industry. However, this concept could only be possible after we find some solutions for the general, labor shortage problem. Specifically, the majority of these challenges stem from improper distribution of labor within each company's divisions. These labor shortages have been influenced by a variety of exogenous (human) variables. The sources of the most serious problems come from the lack of appropriate labor and their fair wages. The work environment is also a contributing factor. These items are considered to be serious challenges to the development of smaller enterprises. The purpose of this study is to explore these difficulties. For solving the labor shortage, enterprises and government should offer employees supportive benefits. Enterprise companies should make an effort to improve their work environments. Companies should also use innovative strategies to raise labor compensation. With this in mind, smaller firms should struggle to retain their employees for an extended period of time and commit to an organizational business strategy. Governments should try to develop a higher recognition of smaller enterprises. They should create human power recruitment, development, and recourse policies as needed. Furthermore, they should manipulate existing policies to support human resource development that aids these companies to be more competitive with larger ones. Additionally, it is necessary to develop new, creative programs to help with the social recognition of smaller enterprises.