• 대한산업공학회지
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• 제41권6호
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• pp.579-587
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• 2015

Semiconductor manufacturing industry is a high density integration industry because it generates a vest number of data that takes about 300~400 processes that is supervised by numerous production parameters. It is asked of engineers to understand the correlation between different stages of the manufacturing process which is crucial in reducing production costs. With complex manufacturing processes, and defect processing time being the main cause. In the past, it was possible to grasp the corelation among manufacturing process stages through the engineer's domain knowledge. However, It is impossible to understand the corelation among manufacturing processes nowadays due to high density integration in current semiconductor manufacturing. in this paper we propose a canonical correlation analysis (CCA) using both wafer test voltage variables and fail bit counts variables. using the method we suggested, we can increase the semiconductor yield which is the result of the package test.

• 한국기계가공학회지
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• 제18권10호
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• pp.110-115
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• 2019

Stationary and rotating blades can be found in a steam turbine generator and the airfoil shapes of these blades can be defined by point data from an aerodynamic design system. The main design process of blades is composed of two steps: first, the blade surface is modeled with the point data; and then, the section data is generated which contains composite curves with line segments and arcs for CAE of the blade. The surface is modeled by a curve-net defined by the point data, which may be extended to obtain the section data to model the blade. This paper presents methods for automating the above-mentioned steps, which have been implemented in the commercial CAD/CAM system, Unigraphics, with API functions written in C-language. Finally, the proposed methods have been applied to model the blade of a steam turbine generator.

• 한국생산제조학회지
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• 제24권2호
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• pp.148-154
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• 2015

Computer aided process planning (CAPP) keeps an important role between the design and manufacturing engineering processes. A CAPP system is a digital link between a computer aided design (CAD) model and manufacturing instructions. CAPP have been researched and applied in manufacturing filed, however, one manufacturing area where CAPP has not been extensively researched is rapid prototyping (RP). RP is a technique for creating directly a three dimensional CAD data into a physical prototype. RP enables to build physical models automatically and to use to reduce the time for the product development cycle as well as to improve the final quality of the designed product. Three-dimensional (3D) printing is one kind of RP that creates three-dimensional objects from CAD models. The paper presents a computer aided process planning system for printing medical products. 3D printing has been used to solve complex medical problems such as surgical instruments, bioengineered products, medical implants, and surgical guides.

• 한국산업보건학회지
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• 제11권3호
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• pp.219-228
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• 2001

Objective : For the purpose of preparing the fundamental data and health promotion and control program on organic solvents in air of manufacturing industry. Methods : The author surveyed number of organic solvent components which was used in working site and also determined the organic solvents concentration in air of 927 manufacturing industries and 1,267 working process with gas chromatography(NIOSH manual) for five years from 1995 to 1999. Results : Mean number of solvents components by type of industry, working process was number of 12. There were exceeded to TLV of 1,2-dichloroethane in textile manufacturing industry N,N-dimethyl furan in tanning and dressing of leather ; luggage, handbags, saddlery, harness and footwear manufacturing industry and chemical and chemical product manufacturing industry by type of industry. There were exceeded to TLV of 1,2-dichloroethane in handwriting and drawing process, cellosolve in adhesive spreading process, N,N-dimethly furan in production of solvent process and adhesion process by working process Total exceeded rate to threshold limit values of organic solvents mixture were 12.9% for EI(Exposure index) and 10.0% for Em(Estimation of mixture) by type of industry, 11.3% for EI and 8.2% for Em by type of working process. The highest exceed rate was 36.7% for EI in tanning and dressing of leather ; luggage handbags, saddlery, harness and footwear manufacturing industry and 29.0% for Em in textile manufacturing industry. The highest exceeded rate was 23.1% for EI and 12.5% for Em in adhesive spreading process by working process. Mean values of total subjects by type of industry and type of working process were $0.7{\pm}1.8$ for EI and $0.7{\pm}1.7$ for Em respectively. Conclusions : As above results, the author suggest that it makes the environmental control program on 1.2-dichloroethane, N,N-dimethyl furan, cellosolve by kind of organic solvent and on textile manufacturing industry, tanning and dressing of leather ; luggage, handbags, saddlery harness and footwear manufacturing industry by type of industry, and on handwriting, drawing process and adhesive spreading process and adhesion process by type of working process.

• 대한안전경영과학회지
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• 제4권2호
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• pp.155-168
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• 2002

As the market and the organizations of an enterprise expand globally, the rapid and accurate communication gets more important for product manufacturing. The manufacturing information flow among the designers, the process planners and the shop floors is characterized and modelled. Its methods are constructed using distributed objects. Their introduction to the network-based CAPP system offers speed and safety for the system and makes the reconstruction and distribution of the application programs easy. The manufacturing processes are generated based on the feature information of a designed part, then the manufacturing resources are selected using the process planning logic which is implemented by distributed objects. The databases and distributed objects are integrated under the recent internet environments. The developed system makes it possible to manipulate and to transfer the process planning and manufacturing data everywhere in the world.

• 한국정밀공학회지
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• 제13권12호
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• pp.63-69
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• 1996

As the significance of quality in the sense of customer satisfaction is growing, the management of quality becomes one of the main interests in the manufacturing systems research. This paper presents the concept of quality-driven CIM(Computer Integrated Manufacturing) system which is composed of a business process domain and a quality domain. In the business process domain, business functions are integrated by conventional design and manufacturing databases on the one hand, and an integrated quality system is interlinked to them via several quality modules on the other hand. Quality information model connects the business process domain with the quality domain where various types of quality data are stored in the form of quality database. This framework helps a manufacturing enterprise to implement the quality-driven CIM system to achieve its final objective "customer satisfaction".ion".uot;.

• 한국기계가공학회지
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• 제20권9호
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.

• 품질경영학회지
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• 제50권4호
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• pp.647-664
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• 2022

Purpose: The purpose of this study is to derive major policies that domestic small and medium-sized manufacturing companies should consider to maximize productivity and quality improvement by utilizing manufacturing data and AI, and to find priorities and implications. Methods: In this study, domestic and international issues and literature review by country were conducted to derive major considerations such as manufacturing AI technology, manufacturing AI talent, manufacturing AI data and manufacturing AI ecosystem. Additionally, the questionnaire survey targeting 46 experts of manufacturing data and AI industry were conducted. Finally, the major considerations and detailed factors importance were derived by applying the Analytic Hierarchy Process (AHP). Results: As a result of the study, it was found that 'manufacturing AI technology', 'manufacturing AI talent', 'manufacturing AI data', and 'manufacturing AI ecosystem' exist as key considerations for domestic manufacturing AI. After empirical analysis, the importance of the four key considerations was found to be 'manufacturing AI ecosystem (0.272)', 'manufacturing AI data (0.265)', 'manufacturing AI technology (0.233)', and 'manufacturing AI talent (0.230)'. The importance of the derived four viewpoints is maintained at a similar level. In addition, looking at the detailed variables with the highest importance for each of the four perspectives, 'Best Practice', 'manufacturing data quality management regime, 'manufacturing data collection infrastructure', and 'manufacturing AI manpower level of solution providers' were found. Conclusion: For the sustainable growth of the domestic manufacturing AI ecosystem, it should be possible to develop and promote manufacturing AI policies in a balanced way by considering all four derived viewpoints. This paper is expected to be used as an effective guideline when developing policies for upgrading manufacturing through domestic manufacturing data and AI in the future.

• 한국인터넷방송통신학회논문지
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• 제18권4호
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• pp.219-226
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• 2018

산업용 사물인터넷(IIoT:Industrial Internet of Thing)은 기존의 공정의 자동화란 범주를 넘어 모든 제조공정을 정보화 하는 것을 의미한다. 또한 각 공정에 설치된 센서로 부터 수집되는 데이터를 토대로 정보화 시스템을 구축하여 각 공정을 실시간으로 관리하고 자동화하여 최적의 생산성을 유지하는데 그 목적을 두고 있다. 각 공정의 센서로 부터 수집되는 데이터는 비정형성을 띄고 있으며 이러한 비정형데이터를 효과적으로 수집하고 처리하기 위해 많은 연구가 이루어지고 있다. 본 논문에서는 효과적인 빅데이터 수집 및 처리를 위하여 미들웨어로 Node-RED를 사용한 시스템을 제안하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.26-29
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• 2003

UV laser micromachining are generally used to create microstructures for micro product through a sequence of lithography-based photopatterning steps. However, the micromachining process is not suitable for the rapid realization of complex microscale 3D product because it depends on worker experiences, excessive cost and time to make many masks. In this paper, the more effective micro rapid manufacturing process, which is developed upon the base of laser micromachining. is proposed to fabricate micro products directly using UV laser ablation and phase change filling. The filling process is useful to hold the micro product during the next ablation step. The proposed micro rapid manufacturing process is also proven experimentally that enables to fabricate the 3D microscale products of UV sensitive polymer from 3D CAD data to functional micro parts.