• Smart Media Journal
• /
• v.8 no.3
• /
• pp.95-103
• /
• 2019

The global manufacturing industry has reached the limit to growth due to a long-term recession, the rise of labor cost and raw material. As a solution to these difficulties, we promote the 4th Industry Revolution based on ICT and sensor technology. Following this trend, this paper proposes the design of a model using manufacturing data in the protection film process for smart manufacturing innovation. In the protective film process, the manufacturing data of temperature, pressure, humidity, and motion and thermal image are acquired by various sensors for the raw material blending, stirring, extrusion, and inspection processes. While the acquired manufacturing data is stored in mass storage, A.I. platform provides time-series image analysis and its visualization.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.24 no.4
• /
• pp.434-440
• /
• 2015

A smart phone is a multimedia device that is a necessity for modern people. It includes a wireless networking system to share information and pictures. However, numerous smart phones are discarded every year, since they have a very fast technology development cycle. This paper presents the development of a telemetry algorithm to measure displacement and strain with a discarded smart phone and digital image correlation methods. To implement the measurement algorithm, the LabVIEW 2010 program development platform was used. In order to verify reliability, an open hole tension test was conducted using a smart phone and a universal test machine. In addition, the measurement results from the smart phone were compared with FEM analysis results.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.8
• /
• pp.104-109
• /
• 2019

Damage caused by wild animals such as pheasants and magpies is a problem in rural areas. A bird repellent system based on sensing and repelling farm pest animals and birds is proposed herein. This system is equipped with a bird model part on a supporting platform and comprises a sound source generator, a system control user interface, and a sensor in the center. The sensor is composed of an illuminance sensor and a PIR sensor. The illuminance sensor distinguishes between day and night, whereas the PIR sensor detects birds or wild animals and outputs them from the sound generator. The entire system can be managed easily by the user interface and system control.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.121-128
• /
• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• Journal of Practical Engineering Education
• /
• v.16 no.1_spc
• /
• pp.1-9
• /
• 2024

The introduction of smart factory digital twins is a concept that has already been proposed to increase productivity in the manufacturing industry through CPS(Cyber Physics System), and has been applied to specific industrial process stages or partially introduced in stages where simulation is required. However, with the recent development of the 4th Industrial Revolution technology, it is receiving attention again along with XR (Extended Reality) technology. However, because there are not many effective cases, this study analyzed the devices, equipment, and technology of the manufacturing process to build a digital twin applying digital threads and synchronized signals and information to control, remote control, and produce intelligent process automation equipment. A platform capable of analyzing information was proposed and developed. Through this, we designed and built an XR content service platform that can support artificial intelligence and developed it to enable control, remote control, and analysis of production information. A possible platform was proposed and developed. We hope that this study will be helpful in conducting research on many cases, and in the future, expanded research on increasing productivity in each part of the process and production is needed through intelligent models.

• Journal of Korea Society of Industrial Information Systems
• /
• v.21 no.2
• /
• pp.1-10
• /
• 2016

In this paper, we consider the algorithms and numerical analysis for real-time integrated control system and resource management of large-scale manufacturing smart factory system. There various data transmitted on Cyber-Physical-System (CPS) is necessary to control in real time, as well as the terminal and the platform with respective system service. This will be a true smart manufacturing which consisting of existing research results, and a numerical analysis by the parameter-specific information. In this paper, Jacoby calculation to reflect the optimization algorithms that are newly proposed. It also presents a behavior that optimal operational algorithm on CPS which is adapted to the sensing data. In addition, we also verify the excellence of the real-time integrated control system through experimentation, by comparison with the existing research results.

• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.2
• /
• pp.41-56
• /
• 2019

Cloud manufacturing is a new concept of manufacturing process that works like a single factory with connected multiple factories. The cloud manufacturing system is a kind of large-scale CPS that produces products through the collaboration of distributed manufacturing facilities based on technologies such as cloud computing, IoT, and virtualization. It utilizes diverse and distributed facilities based on centralized information systems, which allows flexible composition user-centric and service-oriented large-scale systems. However, the cloud manufacturing system is composed of a large number of highly heterogeneous subsystems. It has difficulties in interconnection, data exchange, information processing, and system verification for system construction. In this paper, we derive the user requirements of various aspects of the cloud manufacturing system, such as functional, human, trustworthiness, timing, data and composition, based on the CPS Framework, which is the analysis methodology for CPS. Next, by analyzing the user requirements we define the system requirements including scalability, composability, interactivity, dependability, timing, interoperability and intelligence. We map the defined CPS system requirements to the requirements of oneM2M, which is the platform standard for IoT, so that the support of the system requirements at the level of the IoT platform is verified through Mobius, which is the implementation of oneM2M standard. Analyzing the verification result, finally, we propose a large-scale cloud manufacturing platform based on oneM2M that can meet the cloud manufacturing requirements to support the overall features of the Cloud Manufacturing CPS with dependability.

• Journal of Platform Technology
• /
• v.12 no.2
• /
• pp.3-11
• /
• 2024

In the trend of digital transformation and the increase in non-face-to-face services triggered by the Fourth Industrial Revolution, the demand for cloud computing services is being sharply stimulated. Currently, the cloud is being introduced in various industrial sectors including public, IT, and finance, and the manufacturing industry is also adopting the cloud to secure future sustainability and is promoting innovation through smart manufacturing. However, it has been found that there are constraints in the adoption of cloud by manufacturing companies due to concerns about security. Existing studies that have identified cloud security risks have been limited to presenting general cloud security risks or technical security risks rather than focusing on the manufacturing industry. Therefore, this study aimed to identify cloud security risks in the manufacturing industry based on the actual concerns in the field. For this, expert interviews and literature research were conducted to newly identify cloud security risks in the manufacturing industry, and the adequacy and urgency of the selected security risks were verified through surveys. Based on this study, if a cloud security management system for the manufacturing industry is designed in the future, it is expected that the adoption of cloud in the manufacturing industry will be more activated.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.15 no.3
• /
• pp.59-71
• /
• 2020

This study is empirically intended to look into the effects of smart factory technologies on quality and innovation performance in small and medium-sized Enterprises(SMEs). The research results are as follows. Device and application technologies for smart factory had a positive effect on the information quality and system quality, while platform technologies had an insignificant effect on the information quality and system quality, rejecting the effect of platform technologies for smart factory on information quality and system quality. Device technologies for smart factory had also a significant effect on innovative performance, while platform and application technologies had an insignificant effect on innovative performance, rejecting the effect of platform and application technologies for smart factory on innovative performance. The system quality had a significant effect on innovative performance, while the information quality had an insignificant effect on innovative performance. The quality played a partial mediating role in the effect of device technologies for smart factory on innovative performance. These results indicate that small and medium-sized venture firms should implement a high standard of information quality management(IQM) through interconnection as the kernel of a smart factory in the 4th revolutionary era, and that they can improve their corporate performance through the interlocking between components from manufacturing design to execution and analysis and the integrated management of systematic information collected from devices if necessary.

• Information Systems Review
• /
• v.22 no.4
• /
• pp.185-203
• /
• 2020

With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.