• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1484-1493
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• 2014

Recently, Industry 4.0 (next generation industrial revolution) designed by Germany to retain initiative in manufacturing business is actively studied. Goal of Industry 4.0 is 'Smart factory' which manages progress of production, supply logistics and services. To achieve the goal, we can construct value creation and new business model by integrating organically with production management systems which is existing and cyber-physical systems, Internet of Things, Services Internet and sensor, etc. However, if integration with production management systems does not work effectively by adding and developing new technologies, It does not have performance. Hence, in this research, we will analysis Industry 4.0 which is possible for small quantity batch production and one of the light and flexible manufacturing systems, and based on this, we will suggest methodology to horizontally integrate with production management systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1385-1402
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• 2019

Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.40-45
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• 2019

The smart factory has developed with the help of several technologies such as automation, artificial intelligence, big data, smart sensors and communication protocols. The Internet of things(IOT) among communication protocols has become the key factor for the seamless integration of various manufacturing equipment. Therefore, it is important that the IOT cooperate with the standards of communication protocols proposed by the SEMI in the semiconductor industry. In this paper, we suggest a novel reference model of the communication protocols for semiconductor equipment by introducing an IOT service layer. With the IOT service layer, we can use the functions and the additional services provided by the IOT standards that give the inter-operability between factory machines and host computers. We implement the standard of the communication protocols for semiconductor equipment with the IOT service layer by using ns3 simulator. It concludes that it is necessary to provide the platform for the IOT service layer to deploy efficiently the proposed reference model of the communication protocols.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.127-140
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• 2022

With the recent development of the ICT (information and communication technology), the revolution of the industry has moved on from the third industry to the fourth. There is no doubt that the companies would not survive in the future without adopting these technologies. The purpose of this research is to analyze the intellectual structure of the internet of things(IoT) literature for the Industry 4.0 to suggest a better insight for the field. The data for this research is extracted from the Web of Science database. Total of 1,631 documents and 72,754 references are used for the research with the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure and performed clustering, timeline and burst detection analysis. We identified 12 sub-areas of IoT for the Industry 4.0 which are 'Supply Chain', 'Digital Twin', 'Smart Manufacturing System' and etc. Through the timeline analysis we can find out which clusters will increase or decrease its reputation. As concluding remarks, limitations and further research suggestions are discussed.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.265-275
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• 2024

Smart factory is a remarkable development from traditional manufacturing systems to data-based smart manufacturing systems that can connect and process data continuously, collected from machines, production equipment to production and business processes, capable of supporting workers in making decisions or performing work automatically. Smart factory is the key and center of the fourth industrial revolution, combining improvements in traditional manufacturing activities with digital technology to help factories achieve greater efficiency, contributing to increased revenue and reduce operating costs for businesses. Besides, the importance of smart factories is to make production more quality, efficient, competitive and sustainable. Businesses in Vietnam are in the process of learning and applying smart factory models. However, the number of businesses applying the pine factory model is still limited due to many barriers and difficulties. Therefore, in this paper we conduct a survey to assess the needs and current situation of businesses in applying smart factories and propose some specific solutions to develop and promote application of smart factory model in Vietnamese businesses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4512-4526
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• 2018

The Internet of Things (IoT) has become an emerging industry that is broadly used in many fields from industrial and agricultural manufacturing to home automation and hospitality industry. Because of the sheer number of connected devices transmitting valuable data, the IoT infrastructures have become a main target for cyber-criminals. One of the key challenges in protecting IoT devices is the lack of security measures by design. Although there are many hardware and software based security solutions (firewalls, honeypots, IPDS, anti-virus etc.) for information systems, most of these solutions cannot be applied to IoT devices because of the fact that IoT devices have limited computing resources (CPU, RAM,). In this paper, we propose a honeypot system called HoneyThing for modem/router devices (i.e. a kind of IoT device). HoneyThing emulates TR-069 protocol which is prevalent protocol used to remotely manage customer-premises equipment (CPE) devices, e.g. modems, routers. Honeything also serves an embedded web server simulating a few actual, critical vulnerabilities associated with the implementation of TR-069 protocol. To show effectiveness of the HoneyThing in capturing real world attacks, we have deployed it in the Internet. The obtained results are highly promising and facilitate to reveal network attacks targeting to CPE devices.

• 대한공업교육학회지
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• v.43 no.1
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• pp.158-176
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• 2018

The purpose of this study is to analyze the satisfaction of the manufacturing process and the satisfaction of manufacturing lesson in the lesson of model product manufacturing based on IoT(Internet of Things) for pre-service technology teachers. and we also analyzed 'smart farm' model production manufacturing among various products. The survey questionnaires with 8 questions to investigate satisfaction level of model manufacturing process, difficulties in manufacturing, and the satisfaction level of manufacturing lesson were collected from the 15 pre-service technology teachers and analyzed by using SPSS program. and The results of this study were as follows: First, the lesson satisfaction average level of pre-service technology teachers was high(M=4.22) in model product manufacturing process for the 'smart farm' model making based on the IoT. Second, the average satisfaction level of 'patent search and prior art search report writing education' was as high as 4.07. Therefore, the application of 'prior art search report writing education' showed that it helped to make the product. Third, the best high satisfaction level in the model production manufacturing procedure was 'education of inventive thinking method'(M=4.40). Therefore, the pre-service technology teachers showed that the 'education of inventive thinking methods' was very helpful from the idea design to the optimal selection of idea. The next order of satisfaction level was high(M=4.33) in 'design education and counseling' and 'guidance through selection of professor who guide the production manufacturing in addition to professors who are in charge of lesson'. Because they were helpful in solving the lack of knowledge of pre-service technology teachers. Fourth, satisfaction level with 'the presentation of model making results and exhibitions', 'presentations and participations of external event' was high (M = 4.13). Although the results of interviews with pre-service technology teachers showed that they suffered from lack of knowledge in various technologies, but it was an opportunity to learn things and felt a sense of accomplishment.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.4
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• pp.287-295
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• 2014

Smart manufacturing (SM) considered as a new trend of modern manufacturing helps to meet objectives associated with the productivity, quality, cost and competiveness. It is characterized by decentralized, distributed, networked compositions of autonomous systems. The model of SM is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee's foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To prove this concept, a cloud machining system is considered as research object in which internet of things and cloud computing are used to integrate, organize and allocate the machining resources. Artificial life tools are used for cooperation among autonomous elements in the cloud machining system.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.81-93
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• 2016

Internet of Things (IoT) has been established in various industries and IoT technology is highlighted as a new value creation technology. Especially, Korean government has launched Manufacturing Innovation 3.0 Strategy for developing Smart Factory concept to improve national and corporate's competitiveness. This study tries to present new industry classification scheme considering 10 national key manufacturing industries. Based on the new scheme, 10 national main forces industries are categorized into 6 segments. We have conducted SWOT analysis to comprehend Korean IoT environment. Based on the analysis, we have positioned 6 segments at the strategic decision-making grid to analyze industries' IoT practical usage.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.55-59
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• 2022

Recently, IoT technology has great attention and plays a key role in 4^th industrial revolution in order to design customized products and services. Additive Manufacturing (AM) is applied to fabricate IoT sensor directly or IoT sensor embedded structure. Also, design methods for AM are developing to consolidate various parts of IoT devices. Part consolidation leads to assembly time and cost reduction, reliability improvement, and lightweight. Therefore, a design method was proposed to guide designers to consolidate parts. The design method helps designers to define product architecture that consists of functions and function-part relations. The product architecture is converted to a network graph and then Girvan Newman algorithm is applied to cluster the graph network. Parts in clusters are candidates for part consolidation. To demonstrate the usefulness of the proposed design method, a case study was performed with e-bike fabricated by additive manufacturing.