• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.130-136
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• 2017

The three-wheel pitching machine is a device that throws balls automatically instead of a pitcher and is used chiefly to train baseball players. The machine is abundantly used by people in indoor baseball grounds for baseball games. However, in Korea, foreign products are more popular because the efficiency of domestic products is poor as compared to that of the foreign ones. Therefore, a miniature pitching machine was manufactured to analyze and solve the problems of the existing machine. We added a feeder device to insert the balls in the machine and developed a smart phone application. The machine is easily controlled by a smart phone with bluetooth. While manufacturing the miniature, the existing problems were mitigated and the machine was redesigned for mass production. This study attempted to render the pitching machine more convenient and safer as a substitute for foreign pitching machines.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.173-181
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• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.235-240
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• 2018

ICT converged smart factory started from German Industry 4.0 has been the driving force for the $4^{th}$ Industrial Revolution and the center of manufacturing innovation for major industrial countries. It will be developed according to industry characteristics of each country. Korea is relatively later than other competing countries in the smart factory area. So, the government is establishing related policy and tendering all sorts of supports for smart factory mainly to the small and medium-sized enterprises to spread over the manufacturing industry. It is necessary for government to categorize among similar manufacturing industry and make them share digitalized production information mutually. It will be more effective method for securing global competitiveness than the uniform support. Also, large companies need to establish cloud based production forecasting system over similar industry and share it with other companies rather than expansion of individual smart factory. Mutual development in the manufacturing industry will be realized when the small and medium-sized enterprises and large companies take part in the cooperating ground of smart factory.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.231-235
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• 2012

Manufacturing Information System is a information system which supports the activities such as production planning, workflow management, work stage control. Manufacturing fields are showing new properties in today such as digital information, globalization, integration, to make sophisticated production. In this paper, we descibe major issues in current systems. Eventually, we propose major factors to adapt for new changes and BI systems to support manufacturing production information system based on the major factors.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.1
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• pp.39-47
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• 2015

Globalization, unpredictable markets, increased products customization and frequent changes in products, production technologies and machining systems have become a complexity in today's manufacturing environment. One key strategy for coping with the evolution of this situation is to develop or apply an enable technology such as intelligent manufacturing. Intelligent manufacturing system (IMS) is characterized by decentralized, distributed, networked compositions of heterogeneous and autonomous systems. The model of IMS is inherited from the organization of the living systems in biology and nature so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and selfhealing. To prove this concept, an innovative system with applying the advanced information and communication technology such as internet of things, cognitive agent are proposed to integrate, organize and allocate the machining resources. Innovative system is essential for modern machining system to flexibly and quickly adapt to new challenges of manufacturing environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2539-2544
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• 2014

As the production of electronic goods increases, poor products increase. Smart phone lens has much probability of breakage due to vibration happened at machine during the procedure of production. At this study model of smart phone, robot installed at guide rail is applied by various load according to its mass and investigated with vibration analysis. The analysis result in this study is thought to supply the material necessary at safe design and development on manufacturing machine system of smart phone lens by assembled automation.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.73-85
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• 2020

While Korea became one of manufacturing powers in the world through a fast-follower strategy as well as implementing the approach of advancing manufacturing business focused on quantitative input, The advent of the fourth industrial revolution and demand becoming more complicated than ever both require a system that quickly detects the change of markets in advance and reflects it in the manufacturing strategy. Accordingly, the introduction of a smart factory is not optional but mandatory in order to strengthen the competitiveness of manufacturing business using ICT. This paper aims to investigate key factors having influence on the intention to continuously use a smart factory, the innovative IT device, on the basis of the technology acceptance model. This paper analyzed the influence of the leadership of CEO, organizational learning and perceived switching costs on the intention to continuously use a smart factory by the parameters of perceived ease of use and usefulness, the major belief valuables of the IT acceptance model.

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.98-103
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• 2019

A more accurate method of feature point extraction and matching for three-dimensional reconstruction using low-resolution images of crops is proposed herein. This method is important in basic computer vision. In addition to three-dimensional reconstruction from exact matching, map-making and camera location information such as simultaneous localization and mapping can be calculated. The results of this study suggest applicable methods for low-resolution images that produce accurate results. This is expected to contribute to a system that measures crop growth condition.