• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.299-305
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• 2015

Since the natural disasters such as floods, droughts, heat wave and cold wave are increasing, the need for risk management is necessary to minimize the damage with utilizing IT technology. Also, the monitoring services of disaster response type have been developed and applied. Recently, the open source hardware based on the signal of the sensor, or the monitoring studies have been carried. In this paper, by analyzing a low-cost open source hardware platform such as Beagle board, we examine the utilization of the hardware-based module for sensor monitoring.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.76-83
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• 2019

The South Korean government is actively assisting the supply of the smart factory solutions to SMEs (Small & Medium-sized Enterprises) according to its manufacturing innovation 3.0 policy for the smart manufacturing as the 4th industrial revolution era unfolds. This study analyzed the impacts of the smart factory solutions, which have been supplied by the government, on the companies performances. The effects of the level of smart factory and the operation capabilities for the smart factory solutions on company performances, and the mediating effects of manufacturing capabilities have been analyzed using SPSS and AMOS. The data for this survey-based study were collected from the SMEs which implemented the smart factory solutions since 2015. The results show that the level of smart factory solutions adopted and operation capabilities for the smart factories do not have direct effects on the company performances, but their mediating effects on the manufacturing capabilities matter and the manufacturing capabilities effect directly on the company performances. In addition significant factors boosting the operation capability for the smart factory and the levels of the smart factory solutions are identified. Finally, the policy direction for enhancing the smart factory effects is presented, and the future research directions along with the limitations are suggested.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.583-589
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• 2019

One of the core pillars of the Fourth Industrial Revolution is the innovation of the manufacturing industry. From the beginning, the 4th Industrial Revolution appeared in Germany under the concept of 'Industrial 4.0', which means a radical change in the manufacturing industry that can provide super intelligent product production and services based on artificial intelligence and big data. Since manufacturing innovation is a change in the industrial character of the entire nation, the initial role of government is important. Korea also has various policies related to the 4th Industrial Revolution, but there are still various problems to be solved. Therefore, this paper monitors and analyzes the public R&D projects of the advanced countries on manufacturing innovations in the background mentioned above, and through this, the policy implications are drawn.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.333-339
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• 2022

The purpose of the article is to identify priority trends of technological innovations and strategic opportunities for using the smart potential to the benefit of the Russian industrial production development in the context of digital transformation. The article substantiates the demand for technological process automation at industrial enterprises in Russia and considers the possibilities of using artificial intelligence and the implementation of smart manufacturing in the industry. The article reveals the priorities of the leading Russian industrial companies in the field of digitalization, namely, an expansion of the use of cloud technologies, predictive analysis, IaaS services (virtual data storage and processing centers), supervisory control, and data acquisition (SCADA), etc. The authors give the characteristics of the monitoring of the smart manufacturing systems development indicators in the Russian Federation, conducted by Rosstat since 2020; presents projected data on the assessment of the required resources in relation to the instruments of state support for the development of smart manufacturing technologies for the period until 2024. The article determines targets for the development of smart technologies within the framework of the Federal Project "Digital Technologies".

• Journal of the Economic Geographical Society of Korea
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• v.27 no.2
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• pp.75-94
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• 2024

This study aims to examine changes in the location and spatial structure of the Korean manufacturing industry and to consider the factors that influenced them. From the 1960s to the 1980s, under Korea's export-oriented industrial policy and location policy of large-scale industrial complexes, a manufacturing spatial structure was centered on the Seoul Metropolitan Region and the Southeastern Region. Since the mid-1990s, with the emergence of economic globalization and strengthening corporate competitiveness, technology- and knowledge-intensive manufacturing and R&D activities have been concentrated in the Seoul Metropolitan Region. On the other hand, as the overseas relocation of assembly plants accelerated, the decline of industrial cities in the non-Metropolitan Region progressed. Since the 2010s, manufacturing and start-up activities have become more concentrated in the Seoul Metropolitan Region, showing signs of expanding to the adjacent northern Chungcheong Region. This results from changes in the global value chains followed by overseas relocation of production functions at the global level, and concentration of knowledge-intensive manufacturing and R&D activities in the Seoul Metropolitan Region at the national level, which are reflected in the spatial structure of the manufacturing industry.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.364-372
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• 2007

The cost modeling of the LCD manufacturing system with the repair and the rework process is hard to achieve because of it's complex manufacturing process. The technical cost modeling divides each process separately and hierarchically, so it is very useful to calculate the total manufacturing cost of the complex manufacturing system. We applied the method to the complex LCD manufacturing system to obtain more accurate cost model. Yields are the most important control parameters in manufacturing. In this paper, we propose a yield based cost model for the LCD manufacturing system and reveal the relationship between manufacturing yield and cost. Through the model, we can estimate the manufacturing cost on the basis of yields that are control indicators of manufacturing. Some simulations are performed to observe the effects of the yield to the cost, and the results are coincide with the real situation. With the proposed model, we expect to develop some optimization problems for enlarging productivity in the LCD industry.

• International Journal of Quality Innovation
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• v.6 no.3
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• pp.70-94
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• 2005

The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work-order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the IC packaging industry, this work also proposes a WIP (i.e. work-in-process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.28 no.5
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• pp.217-221
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• 2018

Selective laser melting (SLM) technique is one of the additive manufacturing processes, in which functional, complex parts can be directly manufactured by selective melting layers of powder. SLM technique has received great attention due to offering a facile part-manufacturing route and utilizing a hard-to-manufacturing material (e.g. Ti6Al4V). The SLM process allows the accurate fabrication of near-net shaped parts and the significant reduction in the consumption of raw materials when compared to the traditional manufacturing processes such as casting and/or forging. In this study, we focus the high-speed additive manufacturing of Ti6Al4V parts in the aspect of manufacturing time, controlling various process parameters.

• IE interfaces
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• v.25 no.2
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• pp.276-282
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• 2012

Earned value management(EVM) based progress management was designed to systematically manage large or huge projects with budget based criteria. For this reason, existed methods of EVM based progress management have a practical difficulty to apply to small and medium enterprises(SMEs) not possessing enough human resource, time, and cost. In other words, SMEs have performed simultaneously many small-sized projects emphasizing more project delivery than project budget. This study focuses on the area of project management applying to many small-sized projects simultaneously conducted by SMEs. Thus, the method proposed in this study is to manage only the progress of projects after removing cost factor in order to reduce man powers required for allocating the budget of projects to their all activities in detail in the stage of project planning. This study reveals that SMEs are able to manage progress of many projects easily and intuitively using the proposed method.

• International Journal of Safety
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• v.5 no.1
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• pp.37-41
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• 2006

The major objective of the statistical analysis about industrial accidents is to determine the safety factors so that it is possible to prevent or decrease the number of future accidents by educating those who work in a given industrial field in safety management. So far, however, there exists no quantitative method for evaluating danger related to industrial accidents. Therefore, as a method for developing quantitative evaluation technique, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze features of industrial accidents, a retrospective analysis was performed on 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work was chosen from data related to manufacturing businesses during a three-year period ($2002{\sim}2004$) in Korea. This study used AnswerTree of SPSS and the analysis results enabled us to determine the most important variables that can affect injured people such as the occurrence type, the company size, and the time of occurrence. Also, it was found that the classification system adopted in the present study using QUEST algorithm is quite reliable.