• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.177-182
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• 2017

As major ICT technologies such as IoT, cloud computing, and Big Data are being applied to manufacturing, smart factories are beginning to be built. The key of smart factory implementation is the ability to acquire and analyze data of the factory. Therefore, the need for a big data analysis platform is increasing. The purpose of this study is to construct a platform for big data analysis of manufacturing process and propose integrated method for analysis. The proposed platform is a RHadoop-based structure that integrates analysis tool R and Hadoop to distribute a large amount of datasets. It can store and analyze big data collected in the unit process and factory in the automation system directly in HBase, and it has overcome the limitations of RDB - based analysis. Such a platform should be developed in consideration of the unit process suitability for smart factories, and it is expected to be a guide to building IoT platforms for SMEs that intend to introduce smart factories into the manufacturing process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.135-141
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• 2019

South Korea's smart factory drive is at a very important point. While large-scale funds and manpower are invested to secure international competitiveness and revitalize manufacturing, software investments that are only approached by IT suppliers may end up creating systems that do not meet the actual conditions of the field. As a result, there are problems in the manufacturing sector that can cause consumers to feel the fatigue of innovation in the manufacturing sector. SMEs should check from scratch and establish a gradual integration system so that they can reduce failures in IT investments and implement OT-oriented smart factories that are well utilized in the field. To this end, a process visualization solution was proposed and a step-by-step innovation was proposed at the basic level and the ICT unapplied level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.650-661
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• 2020

The digital transformation of the 4th industrial revolution is leading to changes and innovations in the global economy. Various countries are focusing on reviving their manufacturing industries and economic recovery through smart factories. The purpose of this study is to empirically identify technological determinants for the successful implementation of the smart factory and to verify teose effects on manufacturing operations and the firms' operational/environmental performances. Five factors, including sensor network, platform technology, information system, intelligent automation, and safety, were defined as core technologies. The SEM analysis results of 157 small and medium-sized manufacturing firms that have implemented smart factories are as follows. First, sensor network, platform technology, and information system had significant effects on smart manufacturing operations. Second, smart manufacturing operations have improved firm performance. This study is valuable in that it has confirmed the effectiveness of government-funded projects and systemized key technologies for implementing smart factories. Meanwhile, it is helpful for practitioners to support an efficient and effective decision-making for the new adoption.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.77-87
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• 2021

Smart Factory refers to a factory that can be controlled by itself with an intelligent factory that improves productivity, quality and customer satisfaction by combining the entire process of manufacturing and production with digital automation solutions. The manufacturing industry around the world is rapidly changing, with Germany, Europe, and the United States at the center. In order to cope with such changes, the Korean government is also implementing a policy to spread the supply of smart factories for small and medium-sized companies, and related ministries and agencies such as the Ministry of Commerce, Industry and Energy, the Ministry of SMEs and Venture Business, the Korea Institute of Technology and Information Promotion, and local technoparks, as well as large companies such as Samsung, SK and LG are actively investing in smart manufacturing projects to support smart factories[1]. Factory Automation (FA) construction has many issues regarding the connection of heterogeneous equipment. The most difficult aspect of configuring various communications from various equipment is the reason. Although it may not be known if there are standards or products made up of the same company, it is not easy to build equipment that is old, up-to-date, and different use environments through a series of communications. To solve this problem, we would like to propose a method of communication using Modbus, one of FieldBus, which is one of the many industrial devices of PLC, a representative facility control system, and is used as a communication standard.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.5
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• pp.765-771
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• 2020

Automatic lubrication devices are applied in various fields, such as huge machinery, construction machinery or commercial vehicles, to lower maintenance costs and protect the devices. In addition, the automatic lubrication device reduces frequent component failures cause by friction and allows the machine to replace the lubricating oil replenishment work carried out by the manager. However, the automatic lubricating device used in large machinery or commercial vehicles is relatively large, containing a large amount of lubricant in the space to be lubricated. On the other hand, a smart factory, such as a home appliance or cosmetics factory, lacks space to install large automatic lubrication devices, and it is difficult to distribute electricity. Therefore, there is a need for an automatic lubrication device that can be used in various environments that require lubrication. In this paper, a small automatic lubrication device is proposed for smart factories that have changed parts of existing factories, such as electronics factories, to minimize friction arising from mechanical parts, etc. In particular, the structure of lubricating pumps and component parts that are the core of automatic lubrication devices was described so that they could be utilized in various fields. Finally, a test bed environment is established for the proposed automatic lubrication device to evaluate its performance and verify its applicability.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.113-122
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• 2018

In this paper, IoT(Internet of things) technology, which is the core of the 4th industrial revolution, was applied to the study of reduction of consumption current. The IoT is a sensor that collects data, a sensor communication, a gateway that processes and stores the collected data. Data application of IoT technology is applied to smart home, smart city, healthcare, smart factory, etc. and it needs to be applied to various industrial fields. By sensing the location of the sensor device, the specific functions of the gateway and the platform are turned ON and OFF to reduce the consumption current of the equipment during the OFF period. When the sensor device accesses the gateway, the specific function of the gateway is turned ON and When the device is separated from the gateway, it senses the sensitivity of the wireless signal and automatically turns off the certain functions. As a resurt, it has reduced the consumption of current. In this paper, we propose a novel system for detecting the location of sensor devices by applying IoT technology. The system implementation is realized by software based, and defines the requirements for the implementation of the sensor device gateway. The gateway automatically detects the location, movement of the device and performs necessary functions. Finally verifies the automatic detection performance of the gateway according to the location of the device. It will contribute greatly to the development of the smart city and office.

• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.79-94
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• 2022

Purpose - The purpose of this study is to examine firm-level attributes related to Korean manufacturing small and medium-sized enterprises' (SMEs') decisions to implement smart factories. Design/methodology/approach - This study uses the provided by the Ministry of SMEs and Startups of Korea and the Korea Federation of SMEs. Manufacturing SMEs' decisions to implement smart factories in 2018-2019 were analyzed using multinomial logit and ordered logit models. Findings - The findings of this study suggest that firms' decisions to implement smart factories were positively related to firm size, R&D intensity, international market scope, and transactional relationships with customers. However, smart factory implementation decisions were not related to firm age and CEO gender. Research implications or Originality - This study illuminates firm-level attributes that may drive organizational innovation in the era of Industry 4.0 and thus contributes to the innovation adoption literature. This study also contributes to growing research on smart factories by analyzing the actual, progressive decisions to implement smart factories, as opposed to perceived intentions to implement them.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_1
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• pp.889-896
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• 2020

We describe a new approach to the analyze the control performance of robotic manipulator based on the monitoring system. The structure of monitoring simulator is consist of seven modes such as control state mode, coordinate mode, input/output mode, program mode, parameters mode, and track mode. The applied control algorithme consists of an time varying feed-forward and feedback controller. The proposed scheme is simple in structure, fast in computation, and suitable for real-time implimemtation. Moreover, this scheme does not require any accurate dynamic modeling and values of parameters. Performance of the proposed monitoring system is illustrated by simulation and experiment for robot manipulator with six degrees of freedom.

• Journal of the Korea Safety Management & Science
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• v.26 no.2
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• pp.117-125
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• 2024

The objective of this study is to identify the priority of elements for effective implementation of MES in small and medium-sized manufacturing enterprises trying to develop into smart factories. For this purpose, the Delphi method and the Analytic Hierarchy Process(AHP) mothod are applied. As a result of the study, the cooperation of the members in the supply chain is the most important factor for small and medium-sized enterprises in order to survive in the global competitive environment. Therefore, the enterprises need to make various efforts to create synergies through the technical strength of suppliers and the cooperation in the process of introducing and operating MES.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.1
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• pp.17-27
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• 2018

We propose a new approach to control a biped robot motion based on iterative learning of voice command for the implementation of smart factory. The real-time processing of speech signal is very important for high-speed and precise automatic voice recognition technology. Recently, voice recognition is being used for intelligent robot control, artificial life, wireless communication and IoT application. In order to extract valuable information from the speech signal, make decisions on the process, and obtain results, the data needs to be manipulated and analyzed. Basic method used for extracting the features of the voice signal is to find the Mel frequency cepstral coefficients. Mel-frequency cepstral coefficients are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. The reliability of voice command to control of the biped robot's motion is illustrated by computer simulation and experiment for biped walking robot with 24 joint.