• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.281-286
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• 2013

As the product lifecycle is getting shorter and various models should be released to respond to the needs of customers and markets, automation-based flexible production line has been recognized as the core competitiveness. According to these trends, system vendors supply cell-level systems such as FMC(Flexible Manufacturing Cell) that is integration of core functions of FMS(Flexible Manufacturing System) and RMC(Reconfigurable Manufacturing Cell) that can easily extend components of FMC. In the cell-based environment, flexible management for shop floor composed of existing job shop, FMCs and RMCs from various system vendors has emerged as an important issue. However, there could be some problems on integrated operation between heterogeneous cells to use vendor-specific cell controllers and on seamless information flow with high level systems such as ERP(Enterprise Resource Planning). In this context, this paper proposes process management systems supporting integrated shop operation of heterogeneous multi-cell based flexible manufacturing environment: First of all, (1) Integrated Shop Operation System to apply the process management system is introduced, and (2) Multi-Layer BOP(Bill-Of-Process) model, a backbone of the process management system, is derived with its data structure. Finally, application of the proposed model is illustrated through system implementation results.

• Transactions of Materials Processing
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• v.12 no.2
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• pp.110-115
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• 2003

This paper is concerned with the compression test and forming process of flange by using virtual reality and analysis(simulation) program. This virtual manufacturing can be carried out one personal computer without any expensive devices for experiment. The virtual manufacturing composed of three modules such as the imput, calculation and the output modules on internet. Internet user can give the material's property and process parameters to the sever computer at the input module. On the calculation module, a simulator computes the virtual manufacturing process by analysis program and stores the data as a file. The output module is the program in which internet user can confirm virtual manufacturing results by showing tables, graphs, and 3D animation. This programs is designed by an internet language such as HTML, CGI, VRML and JAVA ,while analysis programs use the finite increasing, the virtual manufacturing technique will substitute many real experiments in the future.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.536-539
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• 2002

The reverse engineering (RE) technology can quickly generate 3D point cloud data of an object by capturing the surface of a model using a 3D scanner. In the rapid prototyping (RP) technology, prototypes are rapidly produced from 3D CAD models in a layer-by-layer additive basis. In this paper, a physical human head shape is duplicated using a new RP process, the Transfer-type Variable Lamination Manufacturing process using expandable polystyrene foam sheet (VLM-ST), after the point cloud data of a human head shape measured from 3D SNX scanner are converted to STL file. From the duplicated human head shape, it has been shown that the VLM-ST process in connection with the 3D scanner is a fast and efficient process in that shapes with free surface, such as the human head shape, can be duplicated with ease. Considering the measurement time and the shape duplication time, the use of 3D SNX scanner and the VLM-ST process is expected to reduce the lead-time fur the development of new products in comparison with the other existing RE-RP connected manufacturing systems.

• 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 Society of Preventive Korean Medicine
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• v.20 no.1
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• pp.111-124
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• 2016

Objectives : Treatment method using drugs has already been used in Korean medicine for a long time. Moreover, database has been developed and utilized for more efficient management of the treatments that use drugs. Most of such database related to knowledge on drugs is composed of origin, efficacy, temperament, ingredients and examples of application of the standardized drugs. Communication with knowledge information in other specialized areas is also accomplished by using the efficacies and ingredients with the drugs. In this study, we aimed to make data structure of the terminologies that represent the manufacturing process of herbs. However, in spite of the fact that the manufacturing process of the drugs imparts effect on their efficacies and ingredients, details of the manufacturing processes are quite limited to simple text sentences, thereby resulting in substantially lower level of utilization and difficulties in systematic researches on various factors included in the manufacturing processes in comparison to other knowledge on drugs. Methods : This Study extracted the factors necessary in the development of database by executing morphological analysis of the manufacturing process of herbs. Results : The factors are 'Order', 'Act', 'Raw material', 'Tools', 'Supporting materials', 'Intensity', 'Duration Time', 'Interval', 'Focus', 'Repetition Number', 'Untill'. We were able to tell the difference of the manufacturing process with a simple structured query language and the factors. Conclusions : Morphological analysis of medicinal herbs manufacturing Process contributes to standardization with information of the manufacturing process. And it helps to creates a quality management system through the Database.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.3
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• pp.54-61
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• 2009

General manufacturing process of the manufacturing time and manufacturing process problems have a problem. In the past, in the manufacturing process the data by hand has been. Therefore, the production performance management information, and materials input, output information, equipment information of the failure of the management problems emerged. Through this research, improvements in real-time production information to collect distribution and overall productivity will increase the efficiency of the system. the production process to improve the quality of management, efficient production methods are presented. is a stable quality control. POP system The new building should be. This is the executive or administrative decisions support. It increases productivity, efficiency, and reduce production costs, increase product reliability. This will increase the company's reputation. This increases the competitiveness of enterprises. POP system toward the future with the new destroyer to prepare for our company. Collectively POP system build this research improves the reliability of the product. Improves the quality of customer service. The expansion of product sales is. increase the competitiveness of enterprises. companies should prepare for the future of the business.

• Journal of the Korean Ceramic Society
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• v.56 no.6
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• pp.596-600
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• 2019

Artificial intelligence with a sufficient amount of realistic big data in certain applications has been demonstrated to play an important role in designing new materials or in manufacturing high-quality products. To reduce cracks in ceramic products using machine learning, it is desirable to utilize big data in recently developed data-driven optimization schemes. However, there is insufficient big data for ceramic processes. Therefore, we developed a numerical algorithm to make "virtual" manufacturing data sets using indirect methods such as computer simulations and image processing. In this study, a numerical algorithm based on the random walk was demonstrated to generate images of cracks by adjusting the conditions of the random walk process such as the number of steps, changes in direction, and the number of cracks.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.121-125
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• 2020

With miniaturization of semiconductor, the manufacturing process become more complex, and undetected small changes in the state of the equipment have unexpectedly changed the process results. Fault detection classification (FDC) system that conducts more active data analysis is feasible to achieve more precise manufacturing process control with advanced machine learning method. However, applying machine learning, especially in supervised learning criteria, requires an arduous data labeling process for the construction of machine learning data. In this paper, we propose a semi-supervised learning to minimize the data labeling work for the data preprocessing. We employed equipment status variable identification (SVID) data and optical emission spectroscopy data (OES) in silicon etch with SF6/O2/Ar gas mixture, and the result shows as high as 95.2% of labeling accuracy with the suggested semi-supervised learning algorithm.

• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.113-127
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• 1996

A various quality data are produced during nuclear fuel fabrication. In order to control quality data efficiently, Computerization of Quality Information System(QIS) using personal computer was established. Database control software and analysis software were developed for QIS. QIS was applied the fuel manufacturing and quality inspection. Quality trend analysis, process control, process capability and quality history docket for nuclear fuel manufacturing were performed by QIS. Through the Quality Information System, quality assurance, quality control, process control and manufacturing engineering were performed efficiently in nuclear fuel manufacturing.