• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.133-138
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• 2005

Automotive pulleys play a key role in driving the cooling pump, oil pump, air-conditioner and so on by using an engine power. Researches on design processes and technologies of the pulleys can be found in many literatures. On the other hand, the areas related to manufacturing processes of the pulleys have been treated negligently. Vast data extracted from various information systems are transformed, integrated, and summarized to become a special database for helping users make a decision. The database, namely the data warehouse has been popularly used in the marketing and customer management of enterprises and recently applied to improve the design and manufacturing processes. In this study the manufacturing process of pulleys were analyzed through the intensive investigation of shop-floors and the interviews with workers and managers. The defects generated during a manufacturing process were categorized in a few types and the causes of defects examined for extracting the dominant parameters in the setup process for producing pulleys. As the first step to construct the data warehouse for the manufacturing processes of pulleys, authors proposed its architecture focused on the reduction of defect rate during the setup process.

• Smart Media Journal
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• v.8 no.3
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• pp.95-103
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• 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 Korea Trade
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• v.25 no.2
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• pp.75-94
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• 2021

Purpose - This article will take the Korean manufacturing industry as an example to estimate Korea's global value chain status from the perspective of overall and sub-industry, hoping to provide a theoretical reference for Korean manufacturing to climb the global value chain. Design/methodology - Based on the WIOD data. The data is calculated by using MATLAB (2014a) coding. The data for 6 sectors are classified according to the International Standard Industrial Classification revision 3 (ISIC Rev. 3), the WIOD data are used to calculate and compare the position, participation and dynamics of the Korea, China and USA' manufacturing industry in the 1995-2016. Findings - The empirical results supported conclusions of the theoretical model. In the Korean GVC of electrical and optical sector, while stronger forward linkages than backward linkages to GVC are advantageous for an average advanced country, the benefits of downstream tasks are pronounced for non-advanced countries. And proved the correlation for an index to capture a country's upstream position or downstream position, it makes sense to compare that Korea's exports of intermediates in the same sector that are used by China and USA. Originality/value - The first is to re-examine the characteristics of South Korea's participation in global value chains under a more systematic and accurate theoretical framework, which provides a new empirical reference for related research; the second is to content covers of the manufacturing 6 sectors, so as to more completely describe the characteristics of Korean manufacturing's participation in global value chains; The value of this paper is providing empirical evidence of the effect of Korea's the GVC of manufacturing sectors. In the GVC of 6 sectors, first three have a higher position in the value chain and are in the upper middle and upper reaches of the GVC. The latter two have a low GVC position index, which has become the main sector that pulls down the overall position of Korea's manufacturing industry.

• IE interfaces
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• v.7 no.3
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• pp.147-154
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• 1994

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.255-269
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• 2008

The increasing dynamic and distributed nature of a business and manufacturing environment makes it hard to collaborate between design and manufacturing parties. The seamless collaboration necessitates a manufacturing quote service (MQS) that delivers manufacturing quotes timely for designer's requests. After envisioning a SOA-inherited collaboration framework, the paper details MQS' functionalities, and syntax and semantics of collaboration messages (i.e., RFQ and manufacturing quote). The MQS is implemented as a Web Service so as to be accessible by designers. For each RFQ, the MQS adaptively generates a responding manufacturing quote by using the DPM library and real-time shop status information. The paper also presents an evolution process that shows the whole process of RQF generation from given product design data. The proposed framework enabled partners to exchange engineering data rapidly and adaptively during the dynamic collaboration, and also increased the benefits of distributed and global production.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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• pp.72-79
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• 1998

In this paper, image processing algorithm is studied to enhance the preciseness of the geometry while converting captured images to CAD data. A program is developed as a result. The code, in the image processing, utilizes outline trace, point data smoothing algorithm. It is capable of automatically generating design data by converting input image data to the CAD data. The output can be made in DXF, IGES formats. The current research can be utilized as a base data for the development of factory automation or flexible manufacturing system which adopt image processing based automatic inspection and measuring system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.210-212
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• 2022

In the manufacturing industry, various sensors are attached to monitor the status of production facility. In many cases, the data obtained through these sensors is time series data. In order to determine whether the status of the production facility is abnormal, the process of extracting patterns from time series data must be preceded. Also various methods for extracting patterns from time series data are studied. In this paper, we use matrix profile algorithm to extract patterns from the collected multivariate time series data. Through this, the pattern of multi sensor data currently being collected from the CNC machine is extracted.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.942-945
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• 2005

This paper tried to analyze the collection and management method of shop-floor information for development of digital framework in u-manufacturing. In detail, the shop-floor information collection method through the direct communication with manufacturing devices using network Including RS-232C/422, field bus and ethernet is analyzed and proposed. In case the direct communication is impossible, the information collection method through additional sensors or data acquisition units is analyzed and proposed. Moreover, the collection method through bar code reader or touch screen of operators is analyzed and proposed to act up to machine to man/mobile/machine.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.574-583
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• 2008

The results of HAPs emission data using TRI (Toxic Release Inventory), SODAM (Source Data Management system) were investigated and the emissions of 7 heavy metals from their sources and emission processes were also analyzed. Questionnaire for source data analysis as well as the stack sampling were carried out for 17 factories among 6 selected industrial types. The annual amount of emissions was estimated based on the measured concentration and flow rates. All sources were operated with high efficiency control devices and the concentration levels of all heavy metals were shown to be below 0.1 to of regulation standard. The highest emission source of heavy metals was steel manufacturing industry with the annual emission of 342.9 kg/yr and followed by hazardous waste incinerator, paint manufacturing, nonferrous metal manufacturing, rolling & press goods manufacturing and storage battery manufacturing. In the case of Hg, the emissions were quite significant from electric acros of steel manufacturing industry, although the concentration level was below the emission standard, showing the necessity of specific care for its management.

• 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.