• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.243-260
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• 2008

To prevent low yields in the semiconductor industry is crucial to the success of that industry. However, to prevent low yields is difficult because of too many factors to affect yield variation and their complex relation in the semiconductor manufacturing process. This study presents a new efficient detection methodology for detecting abnormal yields including high and low yields, which can forecast the yield level of a production unit (namely a lot) based on yield-related feature variables' behaviors. In the methodology, we use C5.0 to identify the yield-related feature variables that are the combination of correlated process variables associated with yield, use SOM (Self-Organizing Map) neural networks to extract and classify significant patterns of past abnormal yield lots and finally use C5.0 to generate classification rules for detecting abnormal yield lot. We illustrate the effectiveness of our methodology using a semiconductor manufacturing company's field data.

• Journal of the Korean Ceramic Society
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• v.36 no.12
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• pp.1327-1334
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• 1999

Behaviors of abnormal expansion during calcination process of Ba2Ti9O20 ceramics and its related effects on the sintering characteristics were investigated as a function of precursors. When BaCO3 and TiO2 powders were used as starting materials. BaTi4O9 phase which has relatively large molar volume was formed drastically with abnormal ex-pansion during the calcination at 95$0^{\circ}C$ to 115$0^{\circ}C$ ON the contrary using BaTiO3 and TiO2 powders as starting materials led to retardation of the formation of BaTi4O9 phase and concurrently suppressed the abnormal expansion during cal-cination process. Especially the calcined powder of BaTiO3 and TiO2 had advantages in the densification and formation of Ba2Ti9O20 single phase in the sintering process.

• Journal of the Korean Ceramic Society
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• v.37 no.7
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• pp.617-624
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• 2000

Abnormal grain growth in alumina was investigated during sinter-HIP process for better understanding of pressure effect on microstructural development. Abnormal grain growth of monolithic alumina was observed near surface region rather than interior region of specimen. Finite element analysis was used to estimate the pressure distribution developed in the specimen. Pressure distribution analysis was in good agreement with grain size distributjion in the specimen. The results of finite element analysis provided that abnormal grain growth monolithic alumina was resulted from the inhomogeneous pressure distribution in the specimen. MgO addition in alumina was effective for the suppression of abnormal grain growth in alumina under inhomogeneous pressure distribution during sinter-HIP process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.34-42
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• 2013

In this study, we develop a method for analyzing business process based on the event-driven process chain (EPC) model. The method consists of five stages such as identifying abnormal events, finding causes for the abnormal events and problems caused by the abnormal events, making cause-and-effect chains, drawing root-cause map, and defining improvement areas. We illustrate how to apply the method with some examples for the domestic registered mail delivery process.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1038-1042
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• 2002

Monitoring of the drill wear and hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process, and provide a relatively easy way to monitor a machining process for industrial application. For this advantage, AE signal is used to estimate the abnormal state. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so on, but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality As the results of this experiment, AE RMS signal and measurements by vision system are shown the similar tendency as abnormal state of drilling. And detection of the abnormal states using BPNs was achieved 96.4% reliability.

• International Journal of Contents
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• v.13 no.2
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• pp.21-28
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• 2017

Abnormal data in the manufacturing process makes it difficult to find useful information that can be applied in data management for the manufacturing industry. It causes various problems in the daily process of production. An issue from the abnormal data can be handled by our method that uses big data and visualization. Visualization is a new technology that transforms data representation into a two-dimensional representation. Nowadays, many newly developed technologies provide data analysis, algorithm, optimization, and high efficiency, and they meet user requirements. We propose combined production of the data visualization approach that uses integrative visualization of sources of abnormal pattern analysis results. The perceived idea of the proposed approach can solve the problem as it also works for big data. It can also improve the performance and understanding by using visualization and solving issues that occur in the manufacturing process with a calendar heat map.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.212-216
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• 1996

Recently, with the development of NC and CNC machine tools and the high labor wage, the cutting process requires the high speed and automatic system which uses industrial robots and the flexible manufacturing system(FMS) that combines several machine tools. In this system, the whole system can be influenced by just one of the machin tools. So it needs to detect a problem and to solve it immediately In in-process state. The monitoring system through measuring the motor current with current sensor has been attracting the attention of lots of researchers view of its low cost and flexibility. By using the pattern discriminant with the detected three-phase-current signal, that is, $I_{RMS}$, a system which can monitor and analyze abnormal machining process condition of the workpiece during the machining will be able to be developed in this research.h.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.1
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• pp.51-56
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• 2015

This paper presents an investigation of abnormal wear of a contact jig between a nail and a nail fixture in electric resistance welding. To perform an analysis on the abnormal wear phenomenon, several methods are provided. Based on the theory of electric resistance welding, are analyzed. Using microscopic analysis, surface craters are observed. In the measurement of the electric current flow in the nail fixture, the current flow distribution is measured. From several analyses, the cause of abnormal wear in the contact jig is measured using the electric discharge of high current density at the inflow point of the electric supply to the nail fixture. An alternative shape for normal wear is proposed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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• pp.8-16
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• 2003

Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.

• Tribology and Lubricants
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• v.24 no.6
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• pp.332-337
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• 2008

This paper presents the surface defect analysis based on the experimental investigation of scribed glasses. The scribing process by a diamond wheel cutter is widely used as a reliable and inexpensive method for sizing of glass sheets. The wheel cutter generates a small median crack on the glass surface, which is then propagated through the glass thickness for complete separation. The surface contour patterns in which are formed during a scribing process are strongly related to wheel cutter parameters such as wheel tip surface finish, tip angle and wheel diameter, and cutting process parameters such as scribing pressure, speed and tooling technique. The scribed surface of a glass sheet provides normal Wallner lines, which represent regular median cracks and crack propagation in glass thickness, and abnormal surface roughness patterns. In this experimental study, normal and abnormal surface topographic patterns are classified based on the surface defect profiles of scribed glass sheets. A normal surface of a scribed glass sheet shows regular Wallner lines with deep median cracks. But some specimens of scribed glass sheets show that abnormal surface profiles of glass sheets in two pieces are represented by a chipping, irregular surface cracks in depth, edge cracks, and combined crack defects. These surface crack patterns are strongly related to easy breakage of the scribed glass imposed by external forces. Thus the scribed glass with abnormal crack patterns should be removed during a quality control process based on the surface defect classification method as demonstrated in this study.